JP2009152881A - Image signal processing circuit, image signal processing apparatus, and image signal processing method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To perform smoothing processing capable of appropriately remove even the noise close to an edge, without having to increase the circuit scale. <P>SOLUTION: An image signal processing circuit which processes an image signal constituted of a plurality of pixels is provided with: a weighting value calculating part 15a which calculates a difference value with a pixel value of a noticing pixel in each peripheral pixel located around the noticing pixel, and sets a value according to magnitude of the calculated difference value as a weighting value; and a pixel addition part 15b which adds the pixel value in each of the peripheral pixels by the ratio, according to the magnitude of the weighting value set by the weighting value calculating part 15a. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to an image signal processing circuit, an image signal processing apparatus including the processing circuit, and an image signal processing method, and more particularly to a technique for reducing noise in an image by adding a plurality of pixel values.

  Conventionally, a technique called image addition is well known as a technique for reducing noise included in an image signal obtained by an image sensor. In the image addition process, a process is performed in which the pixel value (luminance value) of the target pixel is replaced with the addition value of the pixel values of the peripheral pixels in the vicinity region centered on the pixel. As a result, the pixel values are averaged and the image becomes smooth, and unnecessary shade fluctuations due to noise and the like are reduced.

  However, using such a method results in synonymous with the removal of high-frequency components from the image signal by a high-frequency removal filter (so-called LPF: Low Pass Filter), and high-frequency components such as edges in the image are lost. There was a problem that. In order to solve such a problem, there has been proposed a method capable of removing noise while retaining an edge portion in an image. As a specific example, filter processing using a median filter, a bilateral filter, or the like is known.

  For example, by using a median filter, the median value of the pixel values of peripheral pixels in the vicinity region of a certain pixel of interest is replaced with the pixel value of the pixel of interest. As a result, even when an edge exists in the image, the pixel value is not used for the pixel addition operation, and as a result, the edge portion is retained.

Patent Document 1 discloses a technique for removing noise using a median filter.
JP 2000-31314 A

  By the way, when performing image processing using a median filter, it is necessary to always calculate an intermediate value of pixel values in a region near the target pixel. For this reason, there is a problem that processing is troublesome, that is, the circuit scale becomes large.

  On the other hand, the bilateral filter is a filter that changes the weight of pixel addition in accordance with the magnitude of the luminance value, and is added to a portion such as an edge portion where the luminance change with the pixel value of surrounding pixels is steep. Is set to a low weight. As a result, the edge portion in the image is held and the other portions are smoothed, and the noise is reduced. Furthermore, since processing can be performed in one pass, there is also an advantage that the circuit scale can be kept relatively small.

  However, in the bilateral filter, the weight value is set depending on whether or not the difference value from the pixel value of the pixel of interest exceeds a threshold value. It happens that the weight value changes. For example, when the difference value exceeds the threshold value due to noise, the weight value is set to a low value, and the pixel is excluded from the addition target. On the other hand, if the difference value when noise is not present is a value equal to or smaller than the threshold value, the pixel is an addition target.

  When such a process is performed, when the shading level of pixels near the edge changes greatly, especially when the processing target is a moving image, pixels at a specific position such as an edge portion of the image after filtering are noisy. When the removed state and the noise-removed state are repeated and the image is displayed, there is a problem in that a luminance change that appears as if the specific position blinks occurs.

  The present invention has been made in view of such a point, and an object of the present invention is to perform a smoothing process capable of appropriately removing noise in the vicinity of an edge without increasing the circuit scale.

  In the image signal processing circuit that processes an image signal composed of a plurality of pixels, the present invention calculates a difference value between the pixel value of the target pixel in each peripheral pixel located around the target pixel, and calculates the calculated difference A weight value calculation unit that sets a value corresponding to the magnitude of the value as a weight value, and a pixel that adds the pixel values in each of the surrounding pixels at a rate corresponding to the magnitude of the weight value set by the weight value calculation unit And an adding unit.

  By doing in this way, the weight value used for pixel addition comes to be set according to the magnitude of the difference value from the target pixel.

  According to the present invention, it is possible to simultaneously hold an edge and remove noise without using an intermediate value or a threshold value.

  In this case, noise near the edge can also be removed appropriately.

  Hereinafter, a first embodiment of the present invention will be described with reference to FIGS.

  In this example, the image signal processing device is applied to an imaging device. FIG. 1 is a block diagram illustrating an example of an internal configuration of the imaging apparatus according to the present example. An imaging apparatus 100 illustrated in FIG. 1 includes a lens 11, an imaging device 12, an analog signal processing unit 13, an A / D conversion unit 14, an image signal processing unit 15, an encoding unit 16, a D / A conversion unit 17, and an output terminal 18. A control unit 19 and a storage unit 20.

  The lens 11 refracts the subject light and forms an image on a light receiving surface (not shown) of the image sensor 12. The imaging device 12 is composed of a CCD (Charge Coupled Devices) imager or a CMOS (Complementary Metal Oxide Semiconductor) imager, and each light separated into three colors R, G, and B by a color separation prism (not shown) It is converted into a signal corresponding to the amount of light and output as a video signal. The analog signal processing unit 13 includes a CDS (Correlated Double Sampling) circuit, an AGC (Automatic Gain Control) circuit, and the like (not shown). The CDS circuit performs a process of removing reset noise included in the input video signal, and the AGC circuit performs a process of amplifying the video signal and adjusting the signal level to a certain level.

  The analog / digital converter 14 (hereinafter referred to as A / D converter 14) converts the video signal output from the analog signal processor 13 into a digital signal. The image signal processing unit 15 performs processing for reducing noise in the video signal output from the A / D conversion unit 14. In addition, gamma correction for correcting the level of the video signal according to a preset γ curve, feeder back clamp processing for fixing the black level OB (optical black) of the video signal to a constant reference value, white for white balance Perform clip processing. Details of the noise reduction processing will be described later.

  The encoding unit 16 converts the video signal processed by the image signal processing unit 15 into a signal of a predetermined system such as an NTSC (National Television Standards Committee) system or a PAL (Phase Alternating Line) system. A digital / analog converter 17 (hereinafter referred to as a D / A converter 17) converts the video signal output from the encoder 16 into an analog signal. The output terminal 20 is a terminal for outputting the video signal output from the D / A conversion unit 17 to a display unit or a recording unit (not shown).

  The control unit 19 is configured with an MPU (Micro Processing Unit) or the like, and controls each unit configuring the imaging apparatus 100. The storage unit 20 is configured by a ROM (Read Only Memory), a RAM (Random Access Memory), or the like, and stores data being processed by the control unit 19 in addition to storing programs and the like.

  Next, an example of the configuration of the noise reduction processing part in the image signal processing unit 15 will be described with reference to FIGS. 2 and 3. In this example, the noise reduction processing is performed on a target pixel Px as shown in FIG. 3 and a region composed of nine pixels adjacent to the target pixel Px in the vertical and horizontal directions. The area of 9 pixels shown in FIG. 3 is composed of 3 horizontal lines. That is, the line ai composed of the pixel P1, the pixel P2, and the pixel P3 and the lower line, the line ai + 1 composed of the pixel P4, the pixel Px, and the pixel P5, and the pixel P6, the pixel P7, and the pixel P8. It is comprised by the line ai + 2 of the lower stage comprised.

  In this example, a case where a region composed of 3 pixels × 3 pixels is set as an example of processing is described as an example, but the size of the region to be processed is, for example, 5 pixels × 5 pixels or the like. You may set to the magnitude | size of.

  The circuit shown in FIG. 2 shows a configuration example for acquiring each pixel in the arrangement of 3 columns and 3 rows as shown in FIG. The circuit shown in FIG. 2 is provided in the image signal processing unit 15. That is, a line memory LM1 for buffering one line of the input video signal and a line memory LM2 for buffering the video signal for one line output from the line memory LM1 are provided. The line memory LM1 holds and outputs each pixel constituting the line ai + 1 in FIG. 3, and the line memory LM2 holds and outputs each pixel constituting the line ai + 2 in FIG. A pixel output without passing through the line memories LM1 and LM2 is a line ai in FIG.

  Each pixel on each line shown in FIG. 3 is obtained at the same timing by giving a delay of one pixel clock to the input pixel by each of the delay units VL1 to VL6 shown in FIG. That is, in FIG. 2, the video signal input without passing through the line memory LM1 (or LM2) or the delay units VL1 to VL6 is output as the pixel P3 at the right end position in the upper stage (line ai) in FIG. A video signal input only through the part VL1 is output as a pixel P2 at a position adjacent to the left of the pixel P3, and a video signal input through the delay part VL1 and the delay part VL2 is output at a position adjacent to the pixel P2 at the pixel P1. Is output as

  Similarly, the video signal delayed by the line memory LM1 is output as the pixel P5 at the right end position of the middle stage (line ai + 1) in FIG. 3, and the video signal input through the line memory LM1 and the delay unit VL3 is the pixel P5. A video signal that is output as a pixel Px at a position adjacent to the left of the pixel and input through the line memory LM1, the delay unit VL3, and the delay unit VL4 is output as a pixel P4 at a position adjacent to the left of the pixel Px.

  Further, the video signal delayed in the line memory LM1 and the line memory LM2 is output as a pixel P8 at the right end position of the lower stage (line ai + 2) in FIG. The video signal is output as a pixel P7 at a position on the left side of the pixel P8, and the video signal input through the line memory LM1 and the line memory LM2, the delay unit VL5, and the delay unit VL6 is positioned on the left side of the pixel P7. Is output as a pixel P6. In this example, a line memory is used. However, the present invention may be applied to a configuration in which three lines of pixels are output at once using a frame memory.

  The pixel signal of 9 pixels obtained by the circuit configuration shown in FIG. 2 is input to the weight value calculation unit 15a and the pixel addition unit 15b. The weight value calculation unit 15a calculates a difference value from the pixel value of the target pixel Px in each of the peripheral pixels P1 to P8 located around the target pixel Px (see FIG. 3), and sets the magnitude of the calculated difference value. A corresponding value is set as a weight value. Then, the calculated weight value is output to the pixel addition unit 15b. The pixel addition unit 15b adds the difference values in each of the peripheral pixels P1 to P8 at a ratio according to the size of the weight value output from the weight value calculation unit.

  FIG. 4 is a flowchart showing an example of processing of the weight value calculation unit 15a. In FIG. 4, the weight value calculation unit 15a first performs a process of calculating a difference value with respect to the target pixel Px in each of the peripheral pixels P1 to P8 positioned around the target pixel Px (step S1). Then, it is determined whether or not each obtained difference value is larger than a preset constant (step S2).

  If the difference value is larger than the constant, the weight value is set to 0. If the difference value is less than or equal to the constant, the difference value is further subtracted from the constant, and the result is obtained. The value is set as a weight value (step S4).

つまり上記式によれば、差分値ｘが大きければ大きいほど、重み値ｆの値は小さくなる。 When the processing described above is expressed as an expression, the following expression is obtained. In the following equation, the difference value from the target pixel Px is x, and the constant is A.

That is, according to the above equation, the larger the difference value x, the smaller the value of the weight value f.

  The value of the constant A can be freely set by the user, the magnitude of the value is set to a value equal to or lower than the luminance level (edge level) of the signal to be left as a meaningful signal, and the level of the signal to be deleted as noise. Set a value larger than (noise level).

  To explain with a specific example, when the processing target area is composed of each pixel as shown in FIG. 5A, for example, the pixel value of the pixel of interest Px is 8, so the pixel value is Pixels P4, P6, and P7 having a large difference from the target pixel Px, such as 1 and 2, can be regarded as pixels on the other side of the edge as viewed from the target pixel Px. Since the difference value between each pixel on the far side of the edge and each pixel on the far side of the edge is 5 to 7, the edge level in this case is 5 to 7.

  In addition, in the pixel P1, the pixel P2, the pixel P3, the pixel P5, and the pixel P8 determined to be the near side of the edge, the difference between the pixel values is 0 to 1, so 0 to 1 is set as the noise level. In other words, in the case shown in FIG. 5A, by setting the constant A to 5, for example, the pixels having the edge levels of 5 to 7 are held as edges, and in each pixel determined to be on this side of the edge, Noise is removed by pixel addition processing.

  That is, the larger the value of the constant A, the larger the value of the weight value f set for each pixel determined to be beyond the edge. When the value of the constant A is increased, the degree of edge dullness caused by the pixel addition processing of the pixel addition unit 15b increases, but a large amount of noise can be removed accordingly. On the other hand, when the value of the constant A is reduced, the edge is kept clear, but the effect of noise reduction is reduced.

  Next, with reference to FIG. 5, an example of specific processing by the weight calculation unit 15a will be described. FIG. 5A shows a processing area to be subjected to image processing. Similar to the example illustrated in FIG. 3, the processing target region is configured by a total of nine pixels including the target pixel Px and eight peripheral pixels adjacent in the vertical and horizontal directions. In FIG. 5, portions corresponding to those in FIG. 3 are denoted with the same reference numerals.

  In FIG. 5A, the value of the pixel of interest Px is 8, whereas the pixel value of the pixel P4 adjacent to the left of the pixel of interest Px is 2, the pixel value of the diagonally lower left pixel P6 is 1, and the pixel just below Since the pixel value of P7 is 2, and each of these pixels has a large difference from the pixel value of the target pixel Px, these pixels can be regarded as the other side of the edge.

FIG. 5B shows a difference value x (absolute value) from the pixel of interest Px in each of the pixels P1 to P8. As shown in FIG. 5A, the pixel values of the peripheral pixels P1 to P8 are P1 = 8, P2 = 7, P3 = 8, P4 = 2, P5 = 7, P6 = 1, P7 = 2, respectively. , P8 = 8, so the difference value x is
P1: | P1-Px | = | 8-8 | = 0,
P2: | P2-Px | = | 8-7 | = 1
P3: | P3-Px | = | 8-8 | = 0,
P4: | P4-Px | = | 8-2 | = 6,
P5: | P5-Px | = | 8-7 | = 1
P6: | P6-Px | = | 8-1 | = 7,
P7: | P7-Px | = | 8-2 | = 6,
P8: | P8-Px | = | 8-8 | = 0
It becomes.

FIG. 5 (c) shows the result of substituting these difference values x into the equation (1). When the value of the constant A is set to 5, the weight value f in each of the surrounding pixels P1 to P8 is the following value.
P1: A (5) -x (0) = 5,
P2: A (5) -x (1) = 4,
P3: A (5) -x (0) = 5,
P4: A (5) <x (6) ∴ f (x) = 0,
P5: A (5) -x (1) = 4,
P6: A (5) <x (7) ∴ f (x) = 0,
P7: A (5) <x (6) ∴f (x) = 0,
P8: A (5) -x (0) = 5
It becomes. That is, when the magnitude of the difference value x exceeds the constant A, the pixel is not added. On the other hand, while the magnitude of the difference value x does not exceed the constant A, the weight value f increases as the difference value x decreases, and the weight value f decreases as the difference value x increases. The weight value calculation unit 15a outputs the weight value f in each of the surrounding pixels P1 to P8 obtained by performing such processing to the pixel addition unit 15b.

  Next, details of the processing of the pixel addition unit 15b will be described with reference to the flowchart of FIG. In FIG. 6, the pixel addition unit 15 b first calculates the sum of the weight values f in the peripheral pixels of the processing region (Step S <b> 11). Then, the integrated value of the difference value x and the weight value f in each peripheral pixel of the processing region is added (step S12). Further, the sum of the integrated values of the difference value x and the weight value f obtained in step S12 is divided by the total value of the weight values f (step S13).

例えば、図５（ａ）〜（ｃ）に示された注目画素Ｐｘの画素値、差分値ｘ、重み値ｆをこの式に代入すると、７．６５という解が求められる。よって、この値を四捨五入した８が、この処理領域における注目画素の新たな画素値として出力される。 This process is shown as an equation below. In the following formula, the number of peripheral pixels is n, the pixel value of the target pixel Px is ak, and the pixel values of the peripheral pixels P1 to P8 are ai.

For example, when the pixel value, difference value x, and weight value f of the target pixel Px shown in FIGS. 5A to 5C are substituted into this equation, a solution of 7.65 is obtained. Therefore, 8 obtained by rounding off this value is output as a new pixel value of the target pixel in this processing region.

  According to the processing of the weight value calculation unit 15a described above, an area Ar1 that is determined to be beyond the edge, for example, composed of the pixel P4, the pixel P6, and the pixel P7 in FIG. 5 is shown in FIG. Thus, the weight value f is set to 0. For this reason, these pixel values are not included in the object of addition processing in the pixel addition unit 15b. By performing such processing, the edge portion in the image is not smoothed by the pixel addition processing.

  In the embodiment described so far, as a method for calculating the weight value f, the method of providing the constant A and subtracting the difference value x from the constant A is exemplified. However, the weight value f is calculated by other calculation methods. You may make it do. For example, a value obtained by subtracting the difference value in each of the peripheral pixels P1 to P8 from the maximum difference value in the processing region may be set as the weight value. An example of processing in this case is shown as a flowchart in FIG.

  In FIG. 7, the weight value calculation unit 15a first calculates the difference value x in all peripheral pixels in the processing region (step S21). Next, the largest difference value (maximum difference value) is extracted from the calculated difference values x (step S22), and the difference value x is divided from the extracted maximum difference value. Then, the value obtained by the division is set to the weight value f (step S23).

When the above processing is performed on the area shown in FIG. 5A, the maximum difference value obtained in step S22 in FIG. 7 is “7” in the pixel P6 (difference value x in each peripheral pixel). (Refer to FIG. 5B for the value of.) Accordingly, the weight value f set for each of the peripheral pixels P1 to P8 is as follows.
P1: maximum difference value (7) −difference value x (0) = 7,
P2: Maximum difference value (7) −x (1) = 6,
P3: Maximum difference value (7) −x (0) = 7,
P4: Maximum difference value (7) −x (6) = 1,
P5: Maximum difference value (7) −x (1) = 6,
P6: Maximum difference value (7) −x (7) = 0,
P7: Maximum difference value (7) -x (6) = 1,
P8: Maximum difference value (7) −x (0) = 7

  Also by performing such processing, the weight value f in the pixel P4, the pixel P6, and the pixel P7 having a large difference value x from the pixel value of the target pixel Px is set to a small value of 0 or 1. Become.

  Alternatively, the reciprocal of the difference value x may be used as the weight value f. An example of processing of the weight value calculation unit 15a in this case is shown in the flowchart of FIG. In FIG. 8, the weight value calculation unit 15a first calculates a difference value x in each peripheral pixel of the processing region (step S31). Then, it is determined whether or not the difference value x is 0 (step S32). If the difference value x is 0, the weight value f is set to 1 (step S33). If the difference value x is a value other than 0, the reciprocal of the difference value x calculated in step S31. Is set as the weight value f (step S34).

That is, a process of setting a weight value f as a solution of the following equation is performed.

When such a process is performed on the region shown in FIG. 5A, the weight value f in each peripheral pixel is as follows.
P1: 1 / difference value x (0) = 1,
P2: 1 / x (1) = 1,
P3: 1 / x (0) = 1,
P4: 1 / x (6) = 0.17,
P5: 1 / x (1) = 1,
P6: 1 / x (7) = 0.14,
P7: 1 / x (6) = 0.17,
P8: 1 / x (0) = 1
By performing such processing, the weight value f in the pixel P4, the pixel P6, and the pixel P7 having a large difference value x from the pixel value of the target pixel Px is set to a small value less than 1.

  According to the first embodiment described above, since the weight value at the time of pixel addition is set according to the magnitude of the difference value x from the pixel value of the target pixel, the intermediate value of the pixel values of each peripheral pixel is set. There is no need to calculate or provide a threshold.

  Further, since the weight value is obtained by subtracting the difference value x from the pixel value of the target pixel Px from the predetermined constant A, the level of noise removal can be increased by changing the size of the constant A. Can be adjusted. That is, by increasing the value of the constant A, the effect of noise removal can be increased, and by decreasing the value of the constant A, the effect of edge retention can be increased.

  Furthermore, since noise can be removed while retaining the edge, noise in the generated image is not noticeable even when the signal after pixel addition processing is amplified to increase sensitivity.

  Next, a second embodiment of the present invention will be described with reference to FIGS. The imaging apparatus in this example also has the same configuration as the imaging apparatus 100 shown in FIG. According to the second embodiment, isolated points that could not be removed by the configuration and processing according to the first embodiment can be removed.

  In the processing described in the first embodiment, in the case where the target pixel Px itself is an isolated point, the isolated point (noise) cannot be removed by image processing. FIG. 9A illustrates a case where the pixel value of the target pixel Px is 8 in the processing region, while the pixel values of the surrounding pixels P1 to P8 are 1 to 2. In such a case, there is a high possibility that the target pixel Px is an isolated point.

FIG. 9B shows a difference value x between each peripheral pixel shown in FIG. 9A and the pixel value of the target pixel Px on the processing region. As shown in FIG. 9, the difference value x in each peripheral pixel is
P1: | P1-Px | = | 8-1 | = 7,
P2: | P2-Px | = | 8-1 | = 7,
P3: | P3-Px | = | 8-1 | = 7,
P4: | P4-Px | = | 8-2 | = 6,
P5: | P5-Px | = | 8-2 | = 6,
P6: | P6-Px | = | 8-1 | = 7,
P7: | P7-Px | = | 8-2 | = 6,
P8: | P8-Px | = | 8-1 | = 7
It becomes. That is, the entire peripheral pixel is recognized as the other side of the edge.

In this region, when the edge level is 6 to 7, the noise level is 0 to 1, and the formula 1 is used for calculating the weight value, the constant A is set to about 6. The weight value f in each peripheral pixel calculated using the formula 1 is as follows.
P1: A (6) <x (7) ∴ f (x) = 0,
P2: A (6) <x (7) ∴ f (x) = 0,
P3: A (6) <x (7) ∴ f (x) = 0,
P4: A (6) -x (6) = 0,
P5: A (6) -x (6) = 0,
P6: A (6) <x (7) ∴ f (x) = 0,
P7: A (6) -x (6) = 0,
P8: A (6) <x (7) ∴ f (x) = 0
FIG. 9C shows these weight values f on the processing area. That is, since the pixel values of the peripheral pixels P1 to P8 are not used for the addition processing by the pixel addition unit 15b, the output value from the pixel addition unit 15b is 8 (= the pixel value of the target pixel Px). That is, in the processing according to the first embodiment, when the target pixel Px itself is an isolated point, it cannot be removed by image processing.

  In the second embodiment, the difference value x is standardized by further subtracting the minimum difference value in the processing region from the difference value x from the pixel value of the target pixel Px calculated in each peripheral pixel. Yes. By calculating the weight value f using the standardized difference value x, even when the target pixel Px is an isolated point, it can be removed by performing addition processing.

  FIG. 10 is a flowchart showing a processing example of the weight value calculation unit 15b ′ in this example. First, the weight value calculation unit 15b ′ calculates a difference value x from the pixel value of the target pixel Px in all the peripheral pixels P1 to P8 in the processing region (step S41). Next, the difference value (minimum difference value) having the smallest value is extracted from each difference value x calculated in step S41 (step S42).

  Then, in each of the surrounding pixels P1 to P8, a value obtained by subtracting the minimum difference value from the difference value x is set as a new difference value x ′ (step S43), and a weight value f is calculated using the difference value x ′ (step S43). Step S44). For calculating the weight value f, the method of subtracting the difference value x ′ from the preset constant described in the first embodiment (see Equation 1, FIG. 4), or the maximum difference in the processing area A method of subtracting each difference value x ′ from the value (see FIG. 7) and a method of calculating the reciprocal of the difference value x ′ (Equation 3, see FIG. 8) are used.

  For example, a case where the processing shown in FIG. 10 is performed on a processing region in which the target pixel Px itself is suspected of being an isolated point as shown in FIG. 9A will be described as an example. For the calculation of the weight value f, the method of subtracting the difference value x ′ from the constant shown in Equation 1 and FIG. 4 is used.

  The difference values x in the peripheral pixels P1 to P8 in the region shown in FIG. 9A are as shown in FIG. 9B, and P1 = 7, P2 = 7, P3 = 7, P4. = 6, P5 = 6, P6 = 7, P7 = 6, P8 = 7. Since the minimum value among these difference values x is “6”, the minimum difference value (6) is subtracted from each difference value based on the processing of step S43 in FIG.

In each of the surrounding pixels P1 to P8, the difference value x ′ obtained by subtracting the minimum difference value from the difference value x is as follows. FIG. 11A shows the obtained difference value x ′ assigned to the processing area.
P1: difference value x (7) −minimum difference value (6) = 1,
P2: x (7) −minimum difference value (6) = 1,
P3: x (7) −minimum difference value (6) = 1,
P4: x (6) −minimum difference value (6) = 0,
P5: x (6) −minimum difference value (6) = 0,
P6: x (7) −minimum difference value (6) = 1,
P7: x (6) −minimum difference value (6) = 0,
P8: x (7) −minimum difference value (6) = 1

Based on these difference values x ′, when the weight value f is calculated using the equation of Formula 1, the weight value f in each peripheral pixel is as follows. Here, the constant A is 6.
P1: A (6) -x (1) = 5,
P2: A (6) -x (1) = 5,
P3: A (6) -x (1) = 5,
P4: A (6) -x (0) = 6,
P5: A (6) -x (0) = 6,
P6: A (6) -x (1) = 5,
P7: A (6) -x (0) = 6,
P8: A (6) -x (1) = 5
That is, since the weight value f in all the surrounding pixels is a large value, the pixel addition unit 15b performs pixel addition processing based on these weight values f, so that the value output from the pixel addition unit 15b is the peripheral pixel. The pixel value is smoothed. Therefore, even when the target pixel Px is an isolated point, it is deleted by image processing.

  In the case where the target pixel Px is not an isolated point, even if the above-described processing is performed, an effect equivalent to the effect obtained in the processing of the first embodiment can be obtained. For example, the case where the process shown in FIG. 10 is performed for the area composed of each pixel shown in FIG. 5A will be described as an example.

  In the region shown in FIG. 5A, the pixel value of the target pixel Px is 8, and the pixel values of the peripheral pixels are P1 = 8, P2 = 7, P3 = 8, P4 = 2, P5 = 7, respectively. , P6 = 1, P7 = 2, and P8 = 8. The difference value x with respect to the pixel value of the target pixel Px in each of these peripheral pixels is as shown in FIG. 5B, and P1 = 0, P2 = 1, P3 = 0, P4 = 6, P5 = 1, P6 = 7, P7 = 6, and P8 = 0. Therefore, the minimum value among these difference values x is “0”.

That is, since the value does not change even if 0 is subtracted from each difference value x, the weight value f is calculated using these difference values x. When the weight value f is obtained by using the equation (1), the weight value f in each peripheral pixel is as follows. Here, the constant A is 5.
P1: A (5) -x (0) = 5,
P2: A (5) -x (1) = 4,
P3: A (5) -x (0) = 5,
P4: A (5) <x (6) ∴ f (x) = 0,
P5: A (5) -x (1) = 4,
P6: A (5) <x (7) ∴ f (x) = 0,
P7: A (5) <x (6) ∴f (x) = 0,
P8: A (5) -x (0) = 5
That is, the same value as the weight value f (see FIG. 5C) calculated in the first embodiment.

  According to the second embodiment described above, in addition to the effect obtained in the first embodiment, even when the target pixel Px is an isolated point, it is possible to remove it. be able to.

  In this case, prior to pixel addition processing, it is not necessary to perform an operation for removing isolated points in advance using an HPF (High Pass Filter) or the like.

  In the embodiment described so far, the example in which the image signal processing device is adapted to the imaging device has been described. However, the image signal processing device may be applied to other devices such as a television receiver, a video signal recording device, and a video tape recorder. Good.

1 is a block diagram illustrating an internal configuration example of an imaging apparatus according to a first embodiment of the present invention. It is a block diagram which shows the internal structural example of the image signal processing part by the 1st Embodiment of this invention. It is explanatory drawing which shows the example of the process area | region by the 1st Embodiment of this invention. It is a flowchart which shows the process example of the weight value calculation part by the 1st Embodiment of this invention. It is explanatory drawing which shows the example of the process area by the 1st Embodiment of this invention, (a) shows the pixel value in each pixel in a process area, (b) is in a process area (C) is a weight value calculated based on the difference value. It is a flowchart which shows the process example of the pixel addition part by the 1st Embodiment of this invention. It is a flowchart which shows the process example of the weight value calculation part by the modification of the 1st Embodiment of this invention. It is a flowchart which shows the process example of the weight value calculation part by the modification of the 1st Embodiment of this invention. It is explanatory drawing which shows the example of the process area by the 1st Embodiment of this invention, (a) shows the pixel value in each pixel in a process area, (b) is in a process area (C) is a weight value calculated based on the difference value. It is a flowchart which shows the process example of the weight value calculation part by the 2nd Embodiment of this invention. It is explanatory drawing which shows the example of the process area by the 2nd Embodiment of this invention, (a) shows the difference value with the pixel value of the attention pixel in each surrounding pixel in a process area, (B) shows a value obtained by subtracting the minimum difference value in the processing region from the difference value in each peripheral pixel.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 11 ... Lens, 12 ... Image sensor, 13 ... Analog signal processing part, 14 ... A / D conversion part, 15 ... Image signal processing part, 15a ... Weight value calculation part, 15b ... Pixel addition part, 16 ... Encoding part, 17 ... D / A conversion unit, 18 ... output terminal, 19 ... control unit, 20 ... storage unit, LM1 to LM2 ... line memory, VL1 to VL6 ... delay unit, Px ... target pixel, P1 to P6 ... peripheral pixel

Claims (10)

An image signal processing circuit for processing an image signal composed of a plurality of pixels,
A weight value calculation unit that calculates a difference value with the pixel value of the target pixel in each peripheral pixel located around the target pixel, and sets a value according to the magnitude of the calculated difference value as a weight value;
An image signal processing circuit, comprising: a pixel addition unit that adds pixel values in each of the peripheral pixels at a ratio corresponding to a weight value set by the weight value calculation unit. The image signal processing circuit according to claim 1,
The pixel addition unit divides the sum of the weight value and the difference value for each of the peripheral pixels by the sum of the weight values, and the value obtained by the division is the pixel of interest. An image signal processing circuit that outputs a new pixel value. The image signal processing circuit according to claim 2, wherein
The image signal processing circuit, wherein the weight value calculation unit sets a value obtained by subtracting a difference value from a pixel value of the target pixel from a predetermined constant as the weight value. The image signal processing circuit according to claim 3.
The image signal processing circuit, wherein the weight value calculation unit sets the weight value to 0 when a difference value from the pixel value of the target pixel is larger than the constant. The image signal processing circuit according to claim 2, wherein
The weight value calculation unit calculates a difference value from the pixel value of the target pixel in all the surrounding pixels, calculates a maximum value of the difference value in all the surrounding pixels, and in each of the surrounding pixels, An image signal processing circuit characterized in that a value obtained by subtracting a difference value from the pixel value of the target pixel from the maximum value of the difference value is used as the weight value. The image signal processing circuit according to claim 2, wherein
The image signal processing circuit, wherein the weight value calculation unit uses an inverse of a difference value from a pixel value of the target pixel as the weight value. The image signal processing circuit according to claim 6.
The weight value calculation unit sets the weight value to a predetermined value other than 0 when the difference value from the pixel value of the target pixel is 0. The image signal processing circuit according to claim 3.
The pixel addition unit calculates a difference value from the pixel value of the target pixel in all the peripheral pixels, and subtracts a minimum value of the difference value from the difference value as a difference value of each peripheral pixel. An image signal processing circuit. An image signal processing apparatus for processing an image signal composed of a plurality of pixels,
A weight value calculation unit that calculates a difference value with the pixel value of the target pixel in each peripheral pixel located around the target pixel, and sets a value according to the magnitude of the calculated difference value as a weight value;
An image signal processing apparatus comprising: a pixel addition unit that adds pixel values in each of the peripheral pixels at a ratio corresponding to a weight value set by the weight value calculation unit. An image signal processing method for processing an image signal composed of a plurality of pixels,
A weight value calculating step of calculating a difference value with the pixel value of the target pixel in each peripheral pixel located around the target pixel, and setting a value according to the magnitude of the calculated difference value as a weight value;
An image signal processing method comprising: a pixel addition step of adding pixel values in each of the peripheral pixels at a rate corresponding to the set weight value.

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