HK1251387B - Imaging method and device based on dual camera - Google Patents

Description

Dual-camera imaging method and device

Technical Field

The present application relates to the field of image processing technology, and in particular to an imaging method and device based on dual cameras.

Background Art

Dual cameras are increasingly being used in mobile devices. Conventional dual cameras often employ a telephoto lens and a wide-angle lens. The telephoto lens is used to capture photos, while the wide-angle lens assists in calculating depth information for subsequent image blur processing.

However, the dual cameras in the related art have better imaging effects in environments with high brightness and high light, but have poor imaging effects in dark environments.

Summary of the Invention

The present application aims to solve one of the technical problems in the related art at least to a certain extent.

To this end, the present application proposes an imaging method based on dual cameras to improve the imaging effect of dual cameras in low-light environments.

This application proposes an imaging device based on dual cameras.

The present application provides a mobile terminal.

The present application provides a computer-readable storage medium.

To achieve the above objectives, the first embodiment of the present application proposes an imaging method based on a dual camera, wherein the dual camera includes a first camera and a second camera, wherein the resolution of the first camera is higher than that of the second camera, and the sensitivity of the second camera is higher than that of the first camera;

The method comprises the following steps:

Determine the ambient brightness;

Determining a main camera and a secondary camera from the dual cameras according to the ambient brightness;

Using the main camera to shoot a first image, and using the secondary camera to shoot a second image;

generating an imaged image according to the first captured image, and calculating depth information of the imaged image according to the first captured image and the second captured image;

According to the depth information of the imaging image, the imaging image is blurred to obtain the desired target image.

The imaging method based on dual cameras in the embodiment of the present application determines the ambient brightness, and then determines the main camera and the secondary camera from the dual cameras according to the ambient brightness, and uses the main camera to shoot the first captured image, and uses the secondary camera to shoot the second captured image. An imaging image is generated based on the first captured image, and the depth information of the imaging image is calculated based on the first captured image and the second captured image. Then, based on the depth information of the imaging image, the imaging image is blurred to obtain the desired target image. Since a high-resolution camera is used as the first camera and a high-sensitivity camera is used as the second camera, and the first and second cameras are switched between the main and secondary cameras according to the ambient brightness, the performance of the main and secondary cameras can match the current ambient brightness, thereby ensuring the imaging effect, and solving the technical problem of poor imaging effect of dual cameras in dark environments in the prior art.

To achieve the above objectives, a second embodiment of the present application provides an imaging device based on a dual camera, wherein the dual camera includes a first camera and a second camera, wherein the first camera has a higher resolution than the second camera, and the second camera has a higher sensitivity than the first camera; wherein the device includes:

Light metering module, used to determine the ambient brightness;

A switching module, configured to determine a main camera and a secondary camera from the dual cameras according to the ambient brightness;

a shooting module, configured to shoot a first shot image using the main camera, and shoot a second shot image using the auxiliary camera;

a generating module, configured to generate an imaged image according to the first captured image, and calculate depth information of the imaged image according to the first captured image and the second captured image;

The processing module is used to perform blurring processing on the imaging image according to the depth information of the imaging image to obtain the desired target image.

The imaging device based on a dual camera in the embodiment of the present application determines the ambient brightness, and then determines the main camera and the secondary camera from the dual camera according to the ambient brightness, and uses the main camera to shoot the first captured image, and uses the secondary camera to shoot the second captured image. An imaging image is generated based on the first captured image, and the depth information of the imaging image is calculated based on the first captured image and the second captured image. Then, based on the depth information of the imaging image, the imaging image is blurred to obtain the desired target image. Since a high-resolution camera is used as the first camera and a high-sensitivity camera is used as the second camera, and the first and second cameras are switched between the main and secondary cameras according to the ambient brightness, the performance of the main and secondary cameras can match the current ambient brightness, ensuring the imaging effect, and solving the technical problem of poor imaging effect of dual cameras in low-light environments in the prior art.

To achieve the above-mentioned purpose, the third aspect embodiment of the present application proposes a mobile terminal, comprising: a first camera, a second camera, a memory, a processor, and a computer program stored in the memory and runnable on the processor; the resolution of the first camera is higher than that of the second camera, and the sensitivity of the second camera is higher than that of the first camera; when the processor executes the program, the dual-camera-based imaging method as described in the first aspect is implemented.

In order to achieve the above-mentioned objectives, the fourth embodiment of the present application proposes a computer-readable storage medium, which, when executed by a processor, implements the dual-camera-based imaging method as described in the first aspect.

Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and/or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

FIG1 is a schematic diagram of a flow chart of an imaging method based on dual cameras provided in an embodiment of the present application;

FIG2A is a schematic diagram showing the principle of triangulation distance measurement;

FIG2B is a schematic diagram of a disparity map;

FIG3 is a schematic diagram of a flow chart of another dual-camera-based imaging method provided in an embodiment of the present application;

FIG4 is a schematic structural diagram of an imaging device based on dual cameras provided in an embodiment of the present application;

FIG5 is a schematic structural diagram of a terminal device according to another embodiment of the present application;

FIG6 is a schematic diagram of an image processing circuit in one embodiment.

DETAILED DESCRIPTION

The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

The following describes the dual-camera imaging method and device according to an embodiment of the present application with reference to the accompanying drawings.

The execution device of the imaging method of the embodiment of the present application can be a hardware device with dual cameras, such as a mobile phone, a tablet computer, a personal digital assistant, a wearable device, etc. The wearable device can be a smart bracelet, a smart watch, smart glasses, etc.

The hardware device with dual cameras includes a camera module, which includes a first camera and a second camera. The first camera and the second camera each have independent lenses, image sensors, and voice coil motors. The first camera and the second camera are connected to a camera connector, and the voice coil motors are driven by the current provided by the camera connector. The first camera and the second camera are driven by the voice coil motors to adjust the distance between the lenses and the image sensors, thereby achieving focus.

In the dual-camera setup provided in this embodiment, the first camera has a higher resolution than the second camera, and the second camera has a higher sensitivity than the first camera. Therefore, when focusing, only the second camera can be used. When the second camera is in focus, the second drive current value of the second camera's motor is obtained. Then, under the condition that the first and second cameras have the same focus distance, the first drive current value of the first camera's motor is determined based on the second drive current value, and the first camera is driven to focus using the first drive current value. Because the second camera has a lower resolution and faster image processing speed, focusing can be accelerated, resolving the technical issue of slow dual-camera focus speeds in the prior art.

FIG1 is a flow chart of an imaging method based on dual cameras provided in an embodiment of the present application.

As shown in FIG1 , the dual-camera-based imaging method includes the following steps:

Step 101: Determine the ambient brightness.

Specifically, as a possible implementation form, an independent light measuring device may be used to measure the brightness of the environment.

As another possible implementation, the automatically adjusted ISO values of the first and second cameras can be read and the ambient brightness determined based on the read ISO values. Generally, the first and second cameras should use the same ISO value, so that the corresponding ambient brightness can be determined using that ISO value. However, if the ISO values read for the first and second cameras are different, the corresponding ambient brightness can be determined based on the average of the two values.

It should be noted that the ISO value indicates the camera's sensitivity to light. Commonly used ISO values include 50, 100, 200, 400, and 1000. The camera can automatically adjust the ISO value based on the ambient brightness. Therefore, in this embodiment, the ambient brightness can be inferred from the ISO value. Generally, in well-lit conditions, the ISO value is 50 or 100, while in low-light conditions, the ISO value can be 400 or higher.

Step 102: Determine the main camera and the secondary camera from the dual cameras according to the ambient brightness.

Specifically, if the ambient brightness is higher than a threshold brightness, the first camera is used as the main camera and the second camera is used as the secondary camera. If the ambient brightness is not higher than the threshold brightness, the second camera is used as the main camera and the first camera is used as the secondary camera.

This is because when the ambient brightness is below the threshold, the light is insufficient. When using a high-resolution camera as the primary camera to take pictures, more noise will appear, resulting in poor imaging quality. Therefore, when the light is insufficient, you can use a high-sensitivity camera as the primary camera to reduce noise in the image and improve the imaging quality.

On the contrary, when the ambient brightness is higher than the threshold brightness and there is sufficient light, the high-resolution camera has a higher resolution, the image is clearer and has less noise. Therefore, the high-resolution camera can be used as the main camera to take pictures, and the high-sensitivity camera can be used as the secondary camera to calculate more accurate depth information, thereby improving the imaging effect.

Step 103: Use the main camera to capture a first image, and use the auxiliary camera to capture a second image.

Specifically, the main camera and the auxiliary camera are used simultaneously to perform framing and shooting, and a first shot image for imaging and a second shot image for calculating depth information are obtained respectively.

Before shooting, you can preview the image. As a possible implementation method, you can preview only the image captured by the main camera. When the user sees a satisfactory preview image, they click the photo button to control the main camera and the secondary camera to simultaneously frame and shoot.

Step 104 : generating an imaged image according to the first captured image, and calculating depth information of the imaged image according to the first captured image and the second captured image.

Specifically, since the first image and the second image are taken by different cameras respectively, there is a certain distance between the two cameras, resulting in parallax. According to the principle of triangulation, the depth information of the same object in the first image and the second image can be calculated, that is, the distance between the object and the plane where the primary and secondary cameras are located.

In order to explain this process clearly, the principle of triangulation is briefly introduced below.

In real-world scenarios, the human eye primarily relies on binocular vision to discern the depth of a scene. This is similar to the principle behind dual-camera depth resolution. In this embodiment, the depth information of the image is calculated based on the second captured image, primarily relying on the principle of triangulation. Figure 2 illustrates the principle of triangulation.

Based on FIG2A , in the actual space, the imaging object, the positions of the two cameras _OR and _OT , and the focal planes of the two cameras are drawn. The distance f between the focal plane and the plane where the two cameras are located is , and the two cameras perform imaging at the focal plane position, thereby obtaining two captured images.

P and P' are the positions of the same object in different images. The distance from point P to the left edge of the image is X _R , and the distance from point P' to the left edge of the image is _XT . _OR and _OT are two cameras located on the same plane, separated by a distance B.

Based on the principle of triangulation, the distance Z between the object in Figure 2A and the plane where the two cameras are located has the following relationship:

Based on this, we can deduce that d is the distance difference between the positions of the same object in different captured images. Since B and f are constants, the distance Z of the object can be determined based on d.

Of course, in addition to the triangulation method, other methods can also be used to calculate the depth information of the main image. For example, when the main camera and the secondary camera take pictures of the same scene, the distance between the objects in the scene and the camera is proportional to the displacement difference and posture difference of the main camera and the secondary camera imaging. Therefore, in one embodiment of the present application, the above-mentioned distance Z can be obtained based on this proportional relationship.

For example, as shown in Figure 2B, the main image obtained by the main camera and the secondary image obtained by the secondary camera are used to calculate the difference between different points. This is represented by a disparity map, which shows the displacement difference of the same point in the two images. However, since the displacement difference in triangulation positioning is proportional to Z, the disparity map is often directly used as a depth map carrying depth information.

Based on the above analysis, it can be seen that when dual cameras obtain depth information, it is necessary to obtain the position of the same object in different captured images. Therefore, if the two images used to obtain depth information are relatively close, the efficiency and accuracy of depth information acquisition will be improved.

Step 105 : blurring the image according to the depth information of the image to obtain the desired target image.

Specifically, after calculating the depth information of the image, the depth information of each object in the image can be used to determine whether the object is foreground or background. Generally speaking, if the depth information indicates that the object is close to the plane of the primary and secondary cameras and the depth value is small, the object can be determined to be foreground; otherwise, the object is background.

The identified background can be blurred to obtain a target image. In the target image, the foreground is more prominent and the background is blurred, presenting an imaging effect of a focused foreground.

When blurring the background area of an image based on depth information, the following processing methods can be used:

According to the depth information and the focus area, first depth information of the foreground area and second depth information of the background area are obtained, blurring intensity is generated according to the first depth information and the second depth information, and the background area of the imaged image is blurred according to the blurring intensity. Thus, different degrees of blurring are performed according to different depth information, making the blurred image effect more natural and rich in layers.

After focusing on the subject, the depth of field is the spatial depth range that can be clearly imaged by the human eye before and after the focus area where the subject is located. It can be understood that the depth of field range imaged before the focus area is the first depth information of the foreground area, and the depth of field range clearly imaged after the focus area is the second depth information of the background area.

Among them, when blurring, the background area of the image can be blurred in different ways according to the blur intensity:

As a possible implementation method, the blur coefficient of each pixel is obtained based on the blur intensity and the depth information of each pixel in the background area of the imaging image, wherein the blur coefficient is related to the blur intensity, and the larger the blur coefficient, the higher the blur intensity. For example, the blur coefficient of each pixel can be obtained by calculating the product of the blur intensity and the depth information of each pixel in the background area of the imaging image, and then the background area of the imaging image is blurred according to the blur coefficient of each pixel.

As another possible implementation method, since the greater the difference between the second depth information and the depth information of the focus area, the farther the corresponding background area is from the focus area and the less correlated it is, and thus the corresponding blurring intensity is greater, in this example, the correspondence between the difference between the second depth information and the depth information of the focus area and the blurring intensity can be pre-stored. In this correspondence, the greater the difference between the second depth information and the depth information of the focus area, the greater the corresponding blurring intensity. Thus, the difference between the second depth information of the background area of the imaged image and the depth information of the focus area is obtained, and the above correspondence is queried based on the difference to obtain the corresponding blurring intensity, and the background area corresponding to the depth information is blurred based on the blurring intensity.

In this embodiment, after determining the ambient brightness, a primary camera and a secondary camera are determined from the dual camera system based on the ambient brightness. The primary camera is used to capture a first image, and the secondary camera is used to capture a second image. An image is generated based on the first image, and depth information of the image is calculated based on the second image. Based on the depth information of the image, the image is then blurred to obtain the desired target image. By using a high-resolution camera as the first camera and a high-sensitivity camera as the second camera, and switching between the primary and secondary cameras based on the ambient brightness, the performance of the primary and secondary cameras is matched to the current ambient brightness, ensuring excellent imaging quality. This addresses the technical issue of poor imaging quality in low-light environments often encountered with dual cameras in the prior art.

In order to clearly illustrate the previous embodiment, this embodiment provides another imaging method based on dual cameras. FIG3 is a flow chart of another imaging method based on dual cameras provided in this embodiment of the present application.

As shown in FIG3 , the method may include the following steps:

Step 301: Determine the ambient brightness, and determine the main camera and the secondary camera from the dual cameras based on the ambient brightness.

The dual camera includes a first camera and a second camera, the resolution of the first camera is higher than that of the second camera, and the sensitivity of the second camera is higher than that of the first camera.

If the ambient brightness is higher than the threshold brightness, the first camera is used as the main camera and the second camera is used as the secondary camera; if the ambient brightness is not higher than the threshold brightness, the second camera is used as the main camera and the first camera is used as the secondary camera.

For example, the first camera may be a 16M camera, the second camera may be a 5M camera, or a four-in-one 5M camera.

It should be noted that the four-in-one 5M camera is synthesized from four 5M cameras and has better photosensitivity than a single 5M camera.

In step 302 , a first image is captured by the main camera, and a second image is captured by the auxiliary camera.

Specifically, as a possible implementation method, when the ambient brightness is not higher than the threshold brightness, that is, when the ambient brightness is poor, the imaging effect will be affected, resulting in more noise in the images captured by the main camera and the secondary camera.

To improve image quality, multi-frame synthesis noise reduction can be used for image processing on the main camera and the auxiliary camera. Specifically, after determining the main camera and the auxiliary camera, the main camera and the auxiliary camera can be used simultaneously to perform continuous framing and shooting, respectively obtaining n frames of images taken by the main camera and m frames of images taken by the auxiliary camera.

The n frames of images shot by the main camera are synthesized and denoised to obtain a first shot image, and the m frames of images shot by the secondary camera are synthesized and denoised to obtain a second shot image.

In order to facilitate a clear understanding of the multi-frame synthesis noise reduction process, a brief introduction to multi-frame synthesis noise reduction is given below.

When ambient light is insufficient, imaging devices such as mobile terminals typically automatically increase sensitivity. However, this increased sensitivity leads to increased noise in the image. Multi-frame synthesis noise reduction is designed to reduce noise in the image and improve the quality of images captured under high-sensitivity conditions. Its principle is based on the prior knowledge that noise is disordered. Specifically, after continuously capturing multiple frames, the noise appearing at the same location may be red, green, white, or even absent. This provides a comparison and screening method, allowing the pixels corresponding to the same location in the multiple frames to be filtered out. Furthermore, after filtering out the noise, further algorithms can be used to perform color estimation and pixel replacement to effectively remove the noise. This process achieves noise reduction with minimal loss of image quality.

For example, a relatively simple multi-frame synthesis noise reduction method can be used to obtain multiple frames of images, read the values of each pixel corresponding to the same position in the multiple frames, calculate the weighted average of these pixels, and generate the value of the pixel at that position in the synthesized image. In this way, a clear image can be obtained.

Among multiple frames of captured images, there is a frame with the clearest image, which can be used as the base frame. As a possible implementation method, the weight of this base frame can be greater than the weights of other captured images. That is to say, in essence, the function of identifying and removing noise in the base frame is achieved by using other captured images as a reference.

Before performing multi-frame synthesis noise reduction, the number of frames (m) and (n) used for synthesis can be determined based on the ambient brightness. Darker ambient brightness results in more frames being used for synthesis. In other words, m and n are inversely related to ambient brightness. As a possible implementation, m and n have the same value, both ranging from 2 to 6.

For example:

When the ambient brightness level is dark, m=n=6;

When the ambient brightness level is normal, m=n=4;

When the ambient brightness level is bright, m=n=2.

It should be noted that the above-mentioned classification of ambient brightness levels and the values of m and n are only examples and do not constitute a limitation to this embodiment. Those skilled in the art can conceive of determining the best classification method of ambient brightness levels and the values of m and n through a limited number of experiments.

In one possible application scenario, a higher processing speed is required. Since the use of multi-frame synthesis noise reduction will increase the processing time, multi-threaded parallel processing can be considered in this application scenario.

A multi-threaded parallel processing mechanism is started, and n frames of images taken by the main camera are synthesized and denoised by a first thread to obtain a first captured image. At the same time, m frames of images taken by the secondary camera are synthesized and denoised by a second thread to obtain a second captured image.

Step 303 , determine whether the field of view angle of the main camera is less than or equal to the field of view angle of the secondary camera. If so, execute step 304 ; otherwise, execute step 305 .

Specifically, the field of view (FOV) refers to the maximum angle that the lens can cover. If the angle between the scene and the camera exceeds this angle, it will not be imaged. In this embodiment, the field of view of the primary and secondary cameras can be the same or different. However, due to the different field of view values, the difference between the framing of the first captured image and the second captured image is inconsistent, and then some objects are imaged only in one of the first captured image and the second captured image. When calculating the depth, the depth information cannot be calculated for these objects. In order to facilitate the calculation of depth information, in this embodiment, the parts of the first captured image and the second captured image that are the same in framing are cut out as the imaged image as much as possible, so as to ensure the accuracy of the depth information of the imaged image.

Step 304: If the field of view angle of the main camera is less than or equal to the field of view angle of the secondary camera, use the first captured image as the imaged image.

Specifically, if the primary camera's field of view is smaller than or equal to that of the secondary camera, the primary camera's framing range must be smaller than or equal to that of the secondary camera, as the primary and secondary cameras are typically located on the same plane. Therefore, all objects in the first image captured by the primary camera should be included in the second image captured by the secondary camera. In this case, there's no need to crop the first image captured by the primary camera; the first image can be used directly as the final image.

Step 305: If the field of view angle of the main camera is greater than the field of view angle of the secondary camera, an area identical to the viewfinder of the second camera is captured from the first captured image to obtain an image.

Specifically, if the primary camera's field of view is larger than that of the secondary camera, the primary camera's framing range is larger than that of the secondary camera, as the primary and secondary cameras are typically located on the same plane. Consequently, it's possible that objects in the first image captured by the primary camera may not be captured by the secondary camera; in other words, the objects may not exist in the second image. In this case, the first image captured by the primary camera needs to be cropped to capture the same area as the second image's framing range as the final image.

Step 306: Calculate depth information of the imaged image based on the second captured image.

Specifically, the depth information of the imaging image is determined according to the position deviation of the same object in the second captured image and the first captured image, and the parameters of the dual cameras.

For the specific calculation process, please refer to the relevant description of step 104 in the above embodiment, which will not be repeated in this embodiment.

Step 307 : blurring the image according to the depth information of the image to obtain the desired target image.

Specifically, after calculating the depth information of the image, the depth information of each object in the image can be used to determine whether the object is foreground or background. Generally speaking, if the depth information indicates that the object is close to the plane where the primary and secondary cameras are located and the depth value is small, the object can be determined to be foreground; otherwise, the object is background. Furthermore, the identified background can be blurred to obtain the target image.

In this embodiment, after determining the ambient brightness, a primary camera and a secondary camera are determined from the dual camera system based on the ambient brightness. The primary camera is used to capture a first image, and the secondary camera is used to capture a second image. An image is generated based on the first image, and depth information of the image is calculated based on the second image. Based on the depth information of the image, the image is then blurred to obtain the desired target image. By using a high-resolution camera as the first camera and a high-sensitivity camera as the second camera, and switching between the primary and secondary cameras based on the ambient brightness, the performance of the primary and secondary cameras is matched to the current ambient brightness, ensuring excellent imaging quality. This addresses the technical issue of poor imaging quality in low-light environments often encountered with dual cameras in the prior art.

In order to implement the above embodiments, the present application also proposes an imaging device based on dual cameras.

Figure 4 is a schematic diagram of the structure of a dual-camera imaging device provided in an embodiment of the present application. This imaging device can be applied to a mobile terminal with dual cameras. The dual cameras include a first camera and a second camera, wherein the first camera has a higher resolution than the second camera, and the second camera has a higher sensitivity than the first camera.

As shown in FIG. 4 , the imaging device includes a light metering module 41 , a switching module 42 , a shooting module 43 , a generating module 44 and a processing module 45 .

The light measuring module 41 is used to determine the ambient brightness.

Specifically, the light metering module 41 is specifically configured to determine the ambient brightness according to the read ISO values of the first camera and the second camera.

The switching module 42 is configured to determine a main camera and a secondary camera from the dual cameras according to the ambient brightness.

Specifically, the switching module 42 is specifically used to: if the ambient brightness is higher than the threshold brightness, use the first camera as the main camera and the second camera as the secondary camera; if the ambient brightness is not higher than the threshold brightness, use the second camera as the main camera and the first camera as the secondary camera.

The shooting module 43 is configured to shoot a first image using the main camera and shoot a second image using the auxiliary camera.

The generating module 44 is configured to generate an imaged image according to the first captured image, and calculate depth information of the imaged image according to the first captured image and the second captured image.

The processing module 45 is configured to perform blurring processing on the image according to the depth information of the image to obtain a desired target image.

Furthermore, in one possible implementation of the embodiment of the present application, the generation module 44 is specifically configured to, if the field of view angle of the primary camera is less than or equal to the field of view angle of the secondary camera, use the first captured image as the imaging image. If the field of view angle of the primary camera is greater than the field of view angle of the secondary camera, extract the same area from the first captured image as the viewfinder of the second captured image to obtain the imaging image.

It should be noted that the above explanation of the method embodiment is also applicable to the device of this embodiment and will not be repeated here.

In this embodiment, after determining the ambient brightness, a primary camera and a secondary camera are determined from the dual camera system based on the ambient brightness. The primary camera is used to capture a first image, and the secondary camera is used to capture a second image. An image is generated based on the first image, and depth information of the image is calculated based on the first and second images. Based on the depth information of the image, the image is then blurred to obtain the desired target image. By using a high-resolution camera as the first camera and a high-sensitivity camera as the second camera, and switching between the primary and secondary cameras based on the ambient brightness, the performance of the primary and secondary cameras is matched to the current ambient brightness, ensuring imaging quality. This addresses the prior art technical issue of poor imaging quality of dual cameras in low-light environments.

In order to implement the above-mentioned embodiments, the present application also proposes a mobile terminal. Figure 5 is a structural schematic diagram of a terminal device according to another embodiment of the present application. As shown in Figure 5, the terminal device 1000 includes: a shell 1100 and a first camera 1112, a second camera 1113, a memory 1114 and a processor 1115 located in the shell 1100.

The memory 1114 stores executable program code; the processor 1115 runs a program corresponding to the executable program code by reading the executable program code stored in the memory 1114, so as to execute the dual-camera-based imaging method as described in the aforementioned method embodiment.

The resolution of the first camera is higher than that of the second camera, and the sensitivity of the second camera is higher than that of the first camera.

As a possible implementation, the field of view of the first camera is the same as the field of view of the second camera, thereby avoiding the process of intercepting the imaging image from the first captured image and speeding up the image processing speed.

In order to make the first camera have high resolution, a 16M camera may be used. Of course, other high-resolution cameras may also be used, which is not limited in this embodiment.

At the same time, in order to make the second camera have high sensitivity, a four-in-one 5M camera can be used. Of course, other high-sensitivity cameras can also be used, which is not limited in this embodiment.

In order to implement the above embodiments, the present application also proposes a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor of a mobile terminal, implements the imaging method based on dual cameras as in the above embodiments.

The mobile terminal also includes an image processing circuit, which can be implemented using hardware and/or software components and may include various processing units that define an ISP (Image Signal Processing) pipeline. FIG6 is a schematic diagram of the image processing circuit in one embodiment. As shown in FIG6 , for ease of illustration, only the various aspects of the image processing technology relevant to the embodiments of the present application are shown.

As shown in FIG6 , the image processing circuit includes an ISP processor 940 and control logic 950. Image data captured by the imaging device 910 is first processed by the ISP processor 940, which analyzes the image data to capture image statistics that can be used to determine and/or adjust one or more control parameters of the imaging device 910. Specifically, the imaging device 910 may include two cameras, each of which may include one or more lenses 912 and an image sensor 914. The image sensor 914 may include a color filter array (e.g., a Bayer filter) that acquires light intensity and wavelength information captured by each imaging pixel of the image sensor 914 and provides a set of raw image data that can be processed by the ISP processor 940. The sensor 920 may provide the raw image data to the ISP processor 940 based on the interface type of the sensor 920. The sensor 920 interface may utilize an SMIA (Standard Mobile Imaging Architecture) interface, other serial or parallel camera interfaces, or a combination of these interfaces.

The ISP processor 940 processes raw image data on a pixel-by-pixel basis in a variety of formats. For example, each image pixel may have a bit depth of 8, 10, 12, or 14 bits. The ISP processor 940 may perform one or more image processing operations on the raw image data and collect statistical information about the image data. The image processing operations may be performed at the same or different bit depths of precision.

The ISP processor 940 may also receive pixel data from the image memory 930. For example, raw pixel data may be sent from the sensor 920 interface to the image memory 930, and the raw pixel data in the image memory 930 may be provided to the ISP processor 940 for processing. The image memory 930 may be a portion of a memory device, a storage device, or an independent dedicated memory within the electronic device, and may include a DMA (Direct Memory Access) feature.

Upon receiving raw image data from the sensor 920 interface or from the image memory 930, the ISP processor 940 may perform one or more image processing operations, such as temporal filtering. The processed image data may be sent to the image memory 930 for further processing before being displayed. The ISP processor 940 receives processed data from the image memory 930 and processes the processed data in the raw domain as well as in the RGB and YCbCr color spaces. The processed image data may be output to the display 970 for user viewing and/or further processing by a graphics engine or GPU (Graphics Processing Unit). Furthermore, the output of the ISP processor 940 may be sent to the image memory 930, from which the display 970 may read image data. In one embodiment, the image memory 930 may be configured to implement one or more frame buffers. Furthermore, the output of the ISP processor 940 may be sent to the encoder/decoder 960 for encoding/decoding image data. The encoded image data may be stored and decompressed before being displayed on the display 970 device. The encoder/decoder 960 may be implemented by a CPU, a GPU, or a coprocessor.

The statistical data determined by the ISP processor 940 may be sent to the control logic 950 unit. For example, the statistical data may include image sensor 914 statistical information such as auto-exposure, auto-white balance, auto-focus, flicker detection, black level compensation, lens 912 shading correction, etc. The control logic 950 may include a processor and/or microcontroller that executes one or more routines (e.g., firmware) that may determine control parameters of the imaging device 910 and control parameters based on the received statistical data. For example, the control parameters may include sensor 920 control parameters (e.g., gain, integration time for exposure control), camera flash control parameters, lens 912 control parameters (e.g., focal length for focus or zoom), or a combination of these parameters. The ISP control parameters may include gain levels and color correction matrices used for auto-white balance and color adjustment (e.g., during RGB processing), as well as lens 912 shading correction parameters.

In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of such features. Throughout the description of this application, "plurality" means at least two, for example, two, three, etc., unless otherwise specifically defined.

Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application belong.

The logic and/or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and a portable compact disc read-only memory (CDROM). Furthermore, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing it in another suitable manner if necessary, and then storing it in a computer memory.

It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

In addition, the functional units in the various embodiments of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into a module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

The storage medium mentioned above may be a read-only memory, a magnetic disk, or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application. Persons skilled in the art may make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims (10)

1. A dual-camera imaging method, characterized in that the dual-camera comprises a first camera and a second camera, wherein the first camera has a higher resolution than the second camera, and the second camera has a higher sensitivity than the first camera; The method comprises the following steps: Determine the ambient brightness; Determining a main camera and a secondary camera from the dual cameras according to the ambient brightness; The main camera is used to capture n consecutive image frames, and the n consecutive image frames are synthesized and denoised to obtain a first captured image. The secondary camera is used to capture m consecutive image frames, and the m consecutive image frames are synthesized and denoised to obtain a second captured image, wherein n and m are both natural numbers greater than 2, and the values of m and n have an inverse relationship with the ambient brightness. generating an imaged image according to the first captured image, and calculating depth information of the imaged image according to the first captured image and the second captured image; According to the depth information of the imaging image, the imaging image is blurred to obtain the desired target image. 2. The imaging method according to claim 1, wherein determining the primary camera and the secondary camera from the dual cameras based on the ambient brightness comprises: If the ambient brightness is higher than a threshold brightness, the first camera is used as a main camera and the second camera is used as a secondary camera; If the ambient brightness is not higher than the threshold brightness, the second camera is used as the main camera and the first camera is used as the secondary camera. 3. The imaging method according to claim 1, wherein generating an image based on the first captured image comprises: If the field of view angle of the main camera is less than or equal to the field of view angle of the secondary camera, the first captured image is used as the imaging image. 4. The imaging method according to claim 1, wherein generating an image based on the first captured image comprises: If the field of view angle of the main camera is greater than the field of view angle of the secondary camera, an area that is the same as the framing screen of the second camera is intercepted from the first captured image to obtain the imaging image. 5. The imaging method according to any one of claims 1 to 4, wherein determining the ambient brightness comprises: The ambient brightness is determined according to the read ISO values of the first camera and the second camera. 6. A dual-camera imaging device, characterized in that the dual cameras include a first camera and a second camera, the first camera has a higher resolution than the second camera, and the second camera has a higher sensitivity than the first camera; Wherein, the device comprises: Light metering module, used to determine the ambient brightness; A switching module, configured to determine a main camera and a secondary camera from the dual cameras according to the ambient brightness; a shooting module, configured to shoot n consecutive image frames using the main camera, synthesize and reduce noise on the n consecutive image frames to obtain a first shot image, and shoot m consecutive image frames using the secondary camera, synthesize and reduce noise on the m consecutive image frames to obtain a second shot image, wherein n and m are both natural numbers greater than 2, and the values of m and n are both inversely related to the ambient brightness; a generating module, configured to generate an imaged image according to the first captured image, and calculate depth information of the imaged image according to the first captured image and the second captured image; The processing module is used to perform blurring processing on the imaging image according to the depth information of the imaging image to obtain the desired target image. 7. The dual-camera imaging device according to claim 6, wherein the switching module is specifically configured to: If the ambient brightness is higher than a threshold brightness, the first camera is used as a main camera and the second camera is used as a secondary camera; If the ambient brightness is not higher than the threshold brightness, the second camera is used as the main camera and the first camera is used as the secondary camera. 8. A mobile terminal, characterized in that it comprises: a first camera, a second camera, a memory, a processor, and a computer program stored in the memory and executable on the processor; the resolution of the first camera is higher than that of the second camera, and the sensitivity of the second camera is higher than that of the first camera; when the processor executes the program, the dual-camera-based imaging method according to any one of claims 1 to 5 is implemented. 9. The mobile terminal according to claim 8, wherein the field of view angle of the first camera is the same as the field of view angle of the second camera; Among them, the first camera is a 16M camera; the second camera is a 5M camera. 10. A computer-readable storage medium having a computer program stored thereon, wherein when the program is executed by a processor, the dual-camera-based imaging method according to any one of claims 1 to 5 is implemented.