JP2015192179A - White balance adjusting device, photographing device, and white balance adjusting method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a white balance control device capable of stably reducing a color failure in white balance control.SOLUTION: A white balance control device includes: a dividing section for dividing an image which is obtained by imaging a subject, into a plurality of divided regions; a color information generating section for generating color information of the subject for each divided region; a subject luminance calculation section for calculating a subject luminance of the subject for each divided region; a light source estimation section for acquiring light source estimation information including at least one of an estimated light source, reliability and a correction amount for each divided region on the basis of the color information and the subject luminance for each divided region; a white balance coefficient calculation section for calculating a white balance coefficient on the basis of the light source estimation information for each divided region; and a white balance control section which performs white balance control on the image that is obtained by imaging the subject, while using the white balance coefficient.

Description

  The present invention relates to a white balance adjusting device, a photographing device including the white balance adjusting device, and a white balance adjusting method in these devices.

  A general electronic camera is equipped with a white balance adjustment function (auto white balance) for expressing an achromatic object in an achromatic color regardless of the light source color. A well-known white balance adjustment method is to extract information that is assumed to correspond to an achromatic color from the color information of the image obtained from the camera and estimate the light source based on the result of integration or weighted averaging. ing. In this method, information (hereinafter referred to as “white detection frame”) indicating what range of output signals an achromatic object is obtained under each light source is stored, and the color information of the image is white. Based on whether or not it matches the detection frame, it is determined whether or not it corresponds to an achromatic color.

  However, in the above method, there are cases where the object color and the achromatic color cannot be accurately distinguished. A specific example is shown. In many cases, the fluorescent lamp is a green light source that is off the locus of black body radiation. Therefore, in order to adjust the white balance for the light source color of the fluorescent lamp, a white detection frame is set in the green region so as to correspond to the light source, and the color information matching the white detection frame is set to an achromatic color. It is necessary to extract as a subject. However, the light green under the solar light source and the green in the shade have the same color information as the fluorescent lamp, and therefore match the white detection frame of the fluorescent lamp. In such a case, an object color other than an achromatic color under a fluorescent light source is also treated as an achromatic color and white balance adjustment is performed. As a result, there is a problem that the overall tone becomes blue or purple, resulting in undesirable color reproduction (so-called color feria).

  In order to solve such a problem, Patent Documents 1 and 2 propose a method of performing white balance adjustment after determining whether the color information of the green region is an achromatic color or an object color. In the white balance adjustment device described in Patent Document 1, when the pixel to be evaluated has green color information, the average luminance signal Y is compared with a predetermined threshold value. If the average luminance signal Y falls below a predetermined threshold, it is determined that the color is achromatic, and if not, it is determined that the color is an object color and the influence on the white balance adjustment is removed. Moreover, in the image processing apparatus described in Patent Document 2, a light source is estimated based on subject illuminance Bv obtained from information related to exposure and the saturation of a green signal, and whether the object color is under a solar light source or under a fluorescent light source. It is the structure which determines whether it is an achromatic color.

Japanese Patent Application Laid-Open No. 08-077986 JP 2008-072575 A

  However, in the configuration described in Patent Document 1, the average luminance signal Y (that is, relative luminance) obtained from the imaging signal is used for the determination of the achromatic color or the object color. Easy to receive. Extremely speaking, when shooting with a subject that is prone to color failure on the entire screen, the object color may be determined as the light source color, or even if the exposure is overexposed or underexposed even with the same composition The determination of the object color and the achromatic color may be reversed by changing the determination threshold. Further, in the configuration described in Patent Document 2, the subject brightness Bv obtained from the information related to exposure is used. However, the subject brightness Bv in this case is an evaluation value of the entire screen, and therefore the composition and the surrounding subjects are evaluated. It is considered that the dependence is strong and the stability of the judgment is low. In addition, since only the saturation is used as the color information, there is a possibility that the accuracy when estimating the light source is lowered. Therefore, even when the configurations described in Patent Document 1 and Patent Document 2 are used, there is still a possibility that a color feria may occur.

  Furthermore, the problem of color failure also occurs for the white detection frame of a light source other than a fluorescent lamp. For example, an achromatic color under an incandescent light source and a human skin (object color) under a solar light source, an achromatic color and a blue sky (object color) in the shade, and the like. Also for these, it is desired to adjust the white balance after appropriately determining whether the color is an achromatic color or an object color.

  The present invention has been made in view of the above circumstances, and an object thereof is to stably reduce color feria in white balance adjustment.

  A white balance adjustment device according to an embodiment of the present invention includes a dividing unit that divides an image obtained by photographing a subject into a plurality of divided regions, a color information generating unit that generates color information of the subject for each divided region, Based on the subject luminance calculation unit for calculating the subject luminance of the subject for each divided region and the color information and the subject luminance for each divided region, at least one of the estimated light source, reliability, and correction amount is calculated for each divided region. Obtained by photographing a subject using a light source estimation unit that acquires light source estimation information, a white balance coefficient calculation unit that calculates a white balance coefficient based on the light source estimation information for each divided region, and the white balance coefficient And a white balance adjustment unit that adjusts the white balance of the image.

  With this configuration, it is possible to calculate an appropriate white balance coefficient without being affected by the composition and surrounding subjects. As a result, it is possible to perform white balance adjustment processing with less color failure.

  In addition, the subject brightness calculation unit may calculate the subject brightness using the brightness signal of the image for each divided region and the exposure information at the time of subject shooting. Further, the color information and the image luminance signal for each of the divided regions may be generated by performing multiplication of a predetermined white balance coefficient and predetermined linear matrix calculation. This makes it possible to obtain accurate color information and luminance values.

  The light source estimation unit may acquire the light source estimation information using a white detection frame group including a plurality of white detection frames respectively corresponding to a plurality of light sources. Furthermore, at least one of reliability and correction amount may be set in the plurality of white detection frames respectively corresponding to the plurality of light sources.

  The light source estimation unit includes a plurality of white detection frame groups, selects one of the plurality of white detection frame groups according to the subject luminance for each divided region, and uses the selected white detection frame group to generate a light source. The estimation information may be acquired. Further, the plurality of white detection frame groups may be different in at least one of the arrangement of the plurality of white detection frames, the reliability set in the white detection frame, and the correction amount. As a result, it is possible to estimate a light source that is close to the actual subject situation, and it is possible to reduce the influence when it is difficult to estimate the light source.

  The white detection frame group may further include an object color detection frame under a predetermined light source.

  An imaging apparatus according to an embodiment of the present invention includes an imaging unit that captures an image of a subject based on a light beam that has passed through an imaging optical system, and any one of the white balance adjustment devices described above.

  Further, the white balance adjustment method according to the embodiment of the present invention is a method for adjusting the white balance of an image obtained by photographing a subject, and the image obtained by photographing the subject is divided into a plurality of divided regions. A step of generating subject color information for each divided region, a step of calculating subject luminance of the subject for each divided region, and for each divided region based on the color information and subject luminance for each divided region, Using light source estimation information including at least one of estimated light source, reliability, or correction amount, calculating a white balance coefficient based on the acquired light source estimation information, and using the white balance coefficient And adjusting the white balance of the image obtained by photographing the subject.

  According to the white balance adjustment device, the photographing device, and the white balance adjustment method of the present embodiment, the color feria in the white balance adjustment is reduced by more accurately determining the state of the subject and calculating an appropriate white balance coefficient. It becomes possible.

FIG. 1 is a block diagram showing a schematic configuration of a photographing apparatus according to an embodiment of the present invention. FIG. 2 is a functional block diagram of the image processing unit of the photographing apparatus according to the embodiment of the present invention. FIG. 3 is a flowchart showing white balance adjustment processing according to the embodiment of the present invention. FIG. 4 is a diagram showing an example of a white detection frame group for medium luminance used in the white balance adjustment processing according to the embodiment of the present invention. FIG. 5 is a diagram illustrating an example of a high-intensity white detection frame group used in the white balance adjustment processing according to the embodiment of the present invention. FIG. 6 is a diagram showing an example of a white detection frame group for low luminance used in the white balance adjustment processing according to the embodiment of the present invention. FIG. 7 is a table showing an example of light source estimation information obtained in the white balance adjustment process according to the embodiment of the present invention.

  Hereinafter, a photographing apparatus according to an embodiment of the present invention will be described with reference to the drawings. In the following, a digital single lens reflex camera will be described as an embodiment of the present invention. Note that the photographing device is not limited to a digital single lens reflex camera, but includes, for example, a mirrorless single lens camera, a compact digital camera, a camcorder, a tablet terminal, a PHS (Personal Handy phone System), a smartphone, a feature phone, a portable game machine, etc. It may be replaced with another form of device having

[Configuration of the photographing apparatus 1]
FIG. 1 is a block diagram illustrating a schematic configuration of a photographing apparatus 1 according to the present embodiment. As shown in FIG. 1, the photographing apparatus 1 includes a photographing lens 11, an aperture 12, a shutter 13, an image sensor 14, an AGC (Automatic Gain Controller) 15, a signal processing unit 20, an operation unit 30, and an LCD (Liquid Crystal Display). 40, a ROM (Read Only Memory) 50, and a memory card 60. The signal processing unit 20 includes a CPU 21, an image processing unit 22, an image sensor driving unit 23, an aperture / shutter driving unit 24, an LCD control unit 25, and a media interface (hereinafter referred to as “media I / F”) 26. Yes.

  The operation unit 30 includes various switches necessary for the user to operate the photographing apparatus 1, such as a power switch, a release switch, and a photographing mode switch. When the user presses the power switch, power is supplied from the battery (not shown) to each part of the photographing apparatus 1 through the power line. After power is supplied, the CPU 21 accesses the ROM 50, reads out a control program, loads it into a work area (not shown), and executes the loaded control program to control the entire photographing apparatus 1.

  When the release switch is operated, the CPU 21 drives the aperture / shutter so that an appropriate exposure can be obtained based on a photometric value measured by a TTL (Through The Lens) exposure meter (not shown) built in the photographing apparatus 1. The diaphragm 12 and the shutter 13 are driven and controlled via the unit 24. More specifically, drive control of the aperture 12 and the shutter 13 is performed based on an AE function designated by a shooting mode switch, such as a program AE (Automatic Exposure), shutter speed priority AE, aperture priority AE, and the like. The CPU 21 performs AF (Autofocus) control together with AE control. An active method, a phase difference detection method, a contrast detection method, or the like is applied to the AF control. Since the configuration and control of this type of AE and AF are well known, detailed description thereof is omitted here.

  The light flux from the subject passes through the photographing lens 11, the diaphragm 12, and the shutter 13 and is received by the image sensor 14. The image sensor 14 is, for example, a single-plate color CCD (Charge Coupled Device) image sensor having a Bayer pixel arrangement, and is driven based on a vertical synchronization signal and a horizontal synchronization signal supplied from the image sensor driving unit 23. The image sensor 14 accumulates an optical image formed by each pixel on the light receiving surface as a charge corresponding to the amount of light, and generates an image signal corresponding to each color of R (Red), G (Green), and B (Blue). Convert and output to AGC15. Note that the image sensor 14 may be another imager such as a CMOS (Complementary Metal Oxide Semiconductor) image sensor. The AGC 15 amplifies (or attenuates) the imaging signal obtained from the imaging element 14 to a predetermined level and outputs the amplified signal to the image processing unit 22. In another embodiment, the diaphragm 12 or the image sensor 14 may incorporate the function of the shutter 13 or the AGC 15.

  The image processing unit 22 performs predetermined signal processing such as matrix calculation, Y / C separation, white balance adjustment, and the like on the electrical signal (shooting data) input from the image sensor 14 to generate an image signal (luminance signal Y, Color difference signals Cb, Cr) are generated and compressed in a predetermined format such as JPEG (Joint Photographic Experts Group). The image processing unit 22 can communicate with a memory card 60 that is detachably inserted into the card slot via the media I / F 26. The image processing unit 22 stores the generated compressed image signal (photographed image data) in the memory card 60 (or a built-in memory (not shown) provided in the photographing apparatus 1).

  Further, the image processing unit 22 buffers the generated image signal in a frame memory (not shown) in units of frames. The image processing unit 22 sweeps the buffered signal from each frame memory at a predetermined timing, converts it to a video signal of a predetermined format, and outputs it to the LCD control unit 25. The LCD control circuit 25 modulates and controls the liquid crystal based on the image signal input from the image processing unit 22. As a result, the captured image of the subject is displayed on the display screen of the LCD 40. The user can view through the display screen of the LCD 40 a real-time through image captured with appropriate brightness and focus based on AE control and AF control.

  When the user performs a reproduction operation of the captured image, the image processing unit 22 reads the captured image data designated by the operation from the memory card 60 or the built-in memory, converts the image data into an image signal of a predetermined format, and the LCD control unit To 25. The LCD control unit 25 performs modulation control on the liquid crystal based on the image signal input from the image processing unit 22, so that a captured image of the subject is displayed on the display screen of the LCD 40.

[White balance adjustment processing]
Next, white balance adjustment processing in the image processing unit 22 of the present embodiment will be described with reference to FIGS. FIG. 2 is a diagram showing functional blocks related to the white balance adjustment processing of the image processing unit 22, and FIG. 3 is a flowchart showing the flow of white balance adjustment processing. In the following description, “white balance” is expressed as “WB”.

  As shown in FIG. 2, the image processing unit 22 includes an image dividing unit 201, a signal detection unit 202, a luminance signal generation unit 203, a subject luminance calculation unit 204, a color signal generation unit 205, a light source estimation unit 206, and a WB coefficient calculation. Unit 207 and WB adjustment unit 208. These functional units are configured as software executed by the CPU 21, and WB adjustment processing is executed by each functional unit. Note that at least a part of these functional units may be configured by hardware.

  As shown in FIG. 3, in the WB adjustment process of the present embodiment, first, Av (Aperture Value), Tv (Time Value), and Sv (Sensitivity Value) are acquired as exposure information (S1). The acquired information is input to the subject luminance calculation unit 204. Subsequently, the image dividing unit 201 equally divides an image corresponding to all effective pixels of the image sensor 14 into N divided regions (S2). As an example, N = 256, and the screen is divided into 16 horizontal parts × 16 vertical parts.

  Subsequently, 0 is input to n (S3). n is a variable representing the divided area to be processed. Then, it is determined whether n is smaller than N (total number of divided areas) (S4). If n is smaller than N (S4: YES), the signal detection unit 202 integrates the RGB values of the imaging signals in the divided region [n], and R [n], G [n], B [n] Is acquired (S5). R [n], G [n], and B [n] in this case are calculated by averaging the R, G, and B components of all the pixels included in the divided region [n]. Note that the calculation method of R [n], G [n], and B [n] is not limited to the average value, and may be based on other known calculation methods. In addition, pixels such as pixel defects may not be included in the calculation.

Subsequently, in the luminance signal generation unit 203 and the color signal generation unit 205, R [n], G [n], and B [n] in the divided region [n] are converted into the luminance signal Y [n] and the color signal Cx [n. ] And Cy [n] respectively (S6). The calculation method of the luminance signal Y [n] does not matter, but the evaluation value of G [n] may be simply substituted as it is, or may be obtained according to the following equation.
Y [n] = 0.299 × R [n] + 0.587 × G [n] + 0.114 × B [n]

Further, the color signals Cx [n] and Cy [n] are obtained simply by the ratio of the color signals as in the following equation, for example. In the following description, Cx uses the color temperature direction as an axis, and Cy uses the color deviation direction as an axis.
Cx [n] = R [n] / G [n] where G [n] ≠ 0
Cy [n] = B [n] / G [n], where G [n] ≠ 0

Subsequently, the subject brightness calculation unit 204 calculates the subject brightness Bv [n] in the divided area [n] (S7). In the present embodiment, the subject luminance Bv [n] is calculated using Av, Tv, and Sv acquired in S1 and the luminance signal Y [n] acquired in S6. First, the subject brightness Bv ′ photographed under appropriate exposure conditions can be obtained from the following equation.
Ev = Av + Tv
Lv = Bv + Sv
Bv ′ = Lv−Sv = (Av + Tv) −Sv

Since Av, Tv and Sv are known values, Bv ′ is also a known value. Further, as the definition of proper exposure, generally Y = 118 is determined as proper exposure (standard output sensitivity) in an 8-bit system. Accordingly, if the luminance value Y when Y = 118 in the 8-bit system is Yb, the difference Xv from the appropriate exposure can be obtained by the following equation.
Xv = log ₂ (Y / Yb) = log ₂ (Y) −log ₂ (Yb), where Y ≠ 0
That is, the difference Xv [n] in the divided area [n] can be obtained by the following equation.
Xv [n] = log ₂ (Y [n]) − log ₂ (Yb [n]), where Y [n] ≠ 0

Therefore, the subject luminance Bv [n] in the divided region [n] having an arbitrary luminance signal Y [n] can be obtained as in the following equation.
Bv [n] = Bv ′ + Xv [n]

  Subsequently, the light source estimation unit 206 acquires the light source estimation information L [n] in the divided region [n] based on the subject luminance Bv [n] and the color signals Cx [n] and Cy [n]. The light source estimation information L [n] is information used when calculating a WB coefficient, which will be described later, and includes the type of light source to be estimated and its reliability.

  The light source estimation information L [n] is acquired using a white detection frame group including a plurality of white detection frames respectively corresponding to a plurality of light sources. In the present embodiment, there are a plurality of types of white detection frame groups, and one of them is selected according to the subject brightness Bv [n]. Specifically, in the present embodiment, a white detection frame group G1 representing the arrangement of the medium luminance white detection frames shown in FIG. 4, a white detection frame group G2 representing the arrangement of the high luminance white detection frames shown in FIG. And a white detection frame group G3 representing the arrangement of the low-luminance white detection frames shown in FIG. If the subject brightness Bv [n] is smaller than the predetermined low threshold (S8: YES), the white detection frame group G3 for low brightness is selected (S9). On the other hand, when the subject luminance Bv [n] is equal to or higher than a predetermined low threshold (S8: NO) and larger than the predetermined high threshold (S10: YES), the white detection frame group G2 for high luminance is selected ( S11). If the subject brightness Bv [n] is equal to or higher than a predetermined low threshold value (S8: NO) and equal to or lower than a predetermined high threshold value (S10: NO), the medium detection white detection frame group G1 is selected (S12). ). The predetermined low threshold value and high threshold value in this case are set with reference to statistically obtained values.

  Subsequently, the light source estimation information L [n] in the divided region [n] is acquired using the selected white detection frame group (S13). Acquisition of the light source estimation information L [n] will be described with reference to FIGS. In the following description, “color signals Cx [n], Cy [n]” are referred to as “evaluation values”.

  4 to 6, a solid rectangle in the figure represents a white detection frame, and is an area where achromatic colors are distributed under the corresponding light source. A broken-line rectangle is a detection frame that indicates a region in which object colors that are not achromatic colors but are useful for light source estimation and are characteristic are distributed. Each object color detection frame is associated with a predetermined light source. Further, the density of the rectangle is determined so that the reliability of the corresponding light source can be easily understood visually. In the example of the present embodiment, the reliability is determined as low, medium, and high from the order of decreasing density of the rectangle. Further, a curve BR in the figure is a black body radiation locus. As shown in FIGS. 4 to 6, in the present embodiment, the detection frames to be set and the reliability to be set for them are different depending on the white detection frame group.

  For convenience of explanation, first, the white detection frame group G1 selected when the subject luminance Bv [n] is medium luminance will be described with reference to FIG. In the white detection frame group G1 of FIG. 4, the frame 401 is a solar light source, the frame 402 is cloudy, the frame 403 is shaded, the frame 406 is an incandescent lamp, the frame 405 is a warm white light source between the solar light source and the incandescent lamp, A frame 407 is mainly a white detection frame of a fluorescent lamp. A frame 404 is a blue sky, and a frame 408 is a detection frame in which a green object color (such as a plant) is distributed. Further, the frame 404 and the frame 408 are associated with a solar light source.

  When the subject brightness Bv [n] is medium brightness, since the probability of being a solar light source or a fluorescent lamp is statistically high, the reliability of the evaluation values of the frame 401 and the frame 407 is set high. On the other hand, since it is difficult to determine whether it is a blue sky or another object color, the reliability of the frame 404 indicating the blue sky is set low.

  Next, the white detection frame group G2 selected when the subject brightness Bv [n] is high brightness will be described with reference to FIG. In the white detection frame group G2 in FIG. 5, the frame 501 is a solar light source, the frame 502 is cloudy, the frame 503 is shaded, the frame 506 is an incandescent lamp, and the frame 505 is a warm white light source between the solar light source and the incandescent lamp. This is a white detection frame. A frame 504 is a detection frame for a blue sky and a frame 507 is a green object color (for example, a plant). Further, the frame 504 and the frame 507 are associated with a solar light source.

  When compared with the white detection frame group G1 in FIG. 4, as a characteristic point, the first point is that the white detection frame group G2 does not include the white detection frame of the fluorescent lamp. If the subject brightness Bv [n] is high to some extent, the probability of an achromatic color illuminated by a fluorescent lamp is statistically low even if the evaluation value is green. Therefore, when Bv [n] has high luminance, it can be determined that the evaluation value is not a fluorescent lamp.

  The second point is that the reliability of the green object color frame 507 is set high. As described in the first point, since the reliability of the fluorescent lamp is relatively lowered, it is possible to more easily determine whether the evaluation value has a green color or an object color. Become. That is, when Bv [n] has high luminance, it is determined that there is a high possibility that the object color is illuminated by the light source.

  The third point is that the reliability of the blue sky frame 507 is set high. The evaluation value is the same as the second point, but Bv [n] has high brightness and bluish color. The possibility that the evaluation value is blue object color illuminated by some light source color or blue light source color is It is low and it can be judged that there is a high possibility of a blue sky.

  Further, for other light sources, a reliability different from that of the white detection frame group G1 in FIG. 4 can be set based on statistics. In the example of FIG. 5, the reliability of the light source on the low color temperature side is set lower than that of FIG.

  Next, the white detection frame group G3 selected when the subject brightness Bv [n] is low brightness will be described with reference to FIG. In the white detection frame group G3 in FIG. 6, the frame 601 is a solar light source, the frame 602 is cloudy, the frame 603 is shaded, the frame 604 is blue LED illumination, the frame 606 is an incandescent lamp, and the frame 605 is between the solar light source and the incandescent lamp. A warm white light source, frame 607 is a fluorescent lamp, and frame 609 is a white detection frame of a mercury lamp. A frame 608 is a detection frame for a green object color (for example, a plant). Further, the frame 608 is associated with a solar light source.

  When compared with the white detection frame group G1 of FIG. 4, the first point is that the mercury detection white detection frame 609 that did not exist in the white detection frame group G1 exists. Mercury lamps are often used mainly in night street lamps, gymnasiums and stadiums, and achromatic objects illuminated statistically by mercury lamps have a low Bv. Therefore, when the subject brightness Bv [n] is low brightness, a white detection frame of a mercury lamp is added.

  The second point is that in the white detection frame group G3, a white detection frame assuming blue LED illumination is set at the position of the blue sky detection frame 604. Similar to mercury lamps, blue LED lighting is sometimes used for street lamps at night. On the other hand, when the subject brightness Bv [n] is low brightness, the possibility of a blue sky is low. Therefore, the blue sky detection frame 604 is set as a white detection frame for blue LED illumination.

  The third point is that the reliability of the green object color frame 608 is relatively low because the reliability of the white detection frame 607 of the fluorescent lamp is set to be relatively high. The fourth point is that when the subject brightness Bv is relatively low, the probability of being in an indoor environment or the probability of being in a night view is high, so an incandescent lamp frame 606 used as room lighting or warm white used as a street light. The reliability of the frame 605 of the system light source (for example, sodium lamp) is increased.

  Subsequently, the light source estimation information L in the specific evaluation values A and B shown in FIGS. 4 to 6 will be described with reference to FIG. First, regarding the evaluation value A, when the subject luminance Bv is medium luminance or low luminance, the evaluation value A matches the frame 407 or the frame 607. Thereby, the light source is estimated to be a fluorescent lamp, and the light source estimation information L that the reliability is high is acquired. On the other hand, when the subject brightness Bv is high brightness, the evaluation value A matches the frame 507. Thereby, it is estimated that it is a green object color, a light source is a solar light source linked | related with the frame 507, and the light source estimation information L that the reliability is high is acquired.

  Subsequently, for the evaluation value B, when the subject luminance Bv is medium luminance, the evaluation value B matches the frame 404. Thereby, the evaluation value B is a blue sky, and the light source is estimated to be a solar light source, but the light source estimation information L that the reliability is low is acquired. When the subject brightness Bv is high brightness, the evaluation value B matches the frame 504. Thereby, the evaluation value B is a blue sky, the light source is estimated to be a solar light source, and the light source estimation information L that the reliability is high is acquired. Furthermore, when the subject brightness Bv is low, the evaluation value B matches the frame 604. Thereby, the light source is estimated to be blue LED illumination, and the light source estimation information L that the reliability is medium is acquired. Thus, in the present embodiment, the light source estimation information acquired by the subject brightness Bv is different even with the same evaluation value.

  The light source estimation information L [n] acquired as described above is output to the WB coefficient calculation unit 207. Then, 1 is added to n (S14), and the process returns to S4. Thereafter, the processing from S4 to S14 is repeated for all the divided areas, and the light source estimation information L for each divided area is acquired.

  If n exceeds N (S4: YES), the WB coefficient calculation unit 207 calculates the WB coefficient from the light source estimation information L [0: N] in all the divided areas (S15). Here, based on the light source estimation information L, extraction of a white region corresponding to the light source and weighting of the evaluation value based on the reliability are performed, and a WB coefficient (that is, R, G, and B gain) for the entire screen is obtained. Calculate. For example, for the evaluation value A, when the subject luminance Bv is medium luminance, it is determined as an achromatic color under the fluorescent lamp, and the WB coefficient is calculated after doubling the evaluation value. When the subject brightness Bv of the evaluation value B is medium brightness, it is determined as an object color under the solar light source, and the WB coefficient is calculated after multiplying the evaluation value by 0.5. Thus, by setting the reliability, it is possible to reduce the influence on the WB calculation of the evaluation value whose discrimination between the achromatic color and the object color is not clear. If it is difficult to discriminate between object color and achromatic color and estimate the light source, such as when Bv is an evaluation value B of medium luminance, the weight based on the reliability may be set to 0 and excluded from the WB calculation.

  The WB coefficient calculated by the WB coefficient calculation unit is output to the WB adjustment unit 208. Then, the WB adjustment unit 208 performs WB control by multiplying the R, G, and B data of the entire screen by the WB coefficient (S16), and ends the WB adjustment process. The image signal that has undergone the WB adjustment processing is then subjected to other image processing such as edge enhancement processing, and is output from the image processing unit 22.

  As described above, in the present embodiment, the subject luminance Bv and the evaluation value are calculated for each divided area, and the light source estimation information L for each divided area is acquired based on the calculated subject brightness Bv and the evaluation value. It is possible to calculate a WB coefficient with little influence. Further, since a plurality of white detection frame groups corresponding to the subject brightness Bv are provided, the estimation of the light source, the reliability, and the determination of the object color or achromatic color can be set in more detail. As a result, it is possible to perform highly accurate determination close to the actual situation of the photographed subject, and it is possible to reduce color feria by WB adjustment and improve the stability of WB adjustment processing.

  The above is the description of the exemplary embodiments of the present invention. Embodiments of the present invention are not limited to those described above, and various modifications are possible within the scope of the technical idea of the present invention. For example, the embodiment of the present application also includes an embodiment that is exemplarily specified in the specification or a combination of obvious embodiments and the like as appropriate.

  For example, in the above embodiment, in the plurality of white detection frame groups G1 to G3, both the light source and the reliability are different from each other. However, the present invention is not limited to this, and only one of the light source and the reliability is provided. However, a different configuration may be used. Further, in addition to (or instead of) the light source and the reliability, different correction amounts may be set in the plurality of white detection frame groups G1 to G3. Specifically, for example, in the case of a solar light source, the correction amount of the WB adjustment is set to 100% so that the achromatic color is completely white. However, for a light source having a low color temperature, the correction amount is set to 50% because it is preferable to leave the light source color so as to match the appearance of the human eye, instead of correcting it completely white. Therefore, in the examples of FIGS. 4 to 6, since the frame 606 of the low-luminance white detection frame group G3 is highly likely to be an incandescent lamp, the correction amount is set to 50%, and the high-luminance white detection frame group In the G2 frame 406, the correction amount may be set to 25% because there is a possibility of sunset instead of incandescence or the like. In this case, the light source estimation information L further includes a correction amount, and the WB coefficient calculation unit 207 weights the reliability with respect to the evaluation value and calculates the WB coefficient taking the correction amount into consideration.

  Further, the arrangement and reliability of the white detection frames in the white detection frame group are not limited to the above embodiment, and can be arbitrarily set. For example, in the white detection frame group of the above embodiment, only one white detection frame for fluorescent lamps is provided. However, since there are many types of fluorescent lamps, they may be further subdivided. For example, it may be changed depending on whether the method is a three-wavelength type or a normal type, the light source color is daylight, daylight white, white, warm white, or light bulb color. Further, in the white detection frame group in the above embodiment, each detection frame has a clear boundary with each other, but may be overlapped. Furthermore, in the above-described embodiment, the reliability is set to three levels of high, medium, and low. However, more detailed reliability may be set. In the above embodiment, the configuration includes three types of white detection frame groups according to the subject brightness Bv. However, the configuration may include four or more types of white detection frame groups.

Further, the luminance signal Y [n] and the color signals Cx [n], Cy [n] may be obtained by the following equations. Thus, a more suitable evaluation value can be calculated by multiplying a predetermined WB coefficient or adjusting the color balance by linear matrix calculation. In the following equation, GainR, GainG, GainB are predetermined WB coefficients, and C00 to C22 are linear matrix coefficients.

  In the above embodiment, the WB coefficient calculation unit 207 calculates the WB coefficient for the entire screen. However, the WB coefficient may be calculated for each divided area and the WB adjustment may be performed for each divided area.

  Furthermore, in the above-described embodiment, the photographing apparatus that performs the WB adjustment process has been described as an example. However, the present invention is not limited to this, and the WB adjustment process of the above-described embodiment is executed in an independent white balance adjustment apparatus. Also good.

DESCRIPTION OF SYMBOLS 1 Imaging device 11 Shooting lens 12 Aperture 13 Shutter 14 Image sensor 15 AGC
20 signal processing unit 22 image processing unit 30 operation unit 40 LCD
50 ROM
60 memory card

Claims (10)

A dividing unit that divides an image obtained by photographing a subject into a plurality of divided regions;
A color information generation unit that generates color information of a subject for each of the divided regions;
A subject luminance calculation unit for calculating subject luminance of the subject for each of the divided regions;
A light source estimation unit that acquires light source estimation information including at least one of an estimated light source, reliability, and correction amount for each of the divided regions based on color information and subject luminance for each of the divided regions;
A white balance coefficient calculation unit that calculates a white balance coefficient based on the light source estimation information for each divided region;
A white balance adjustment device, comprising: a white balance adjustment unit that performs white balance adjustment of an image obtained by photographing the subject using the white balance coefficient.   The white balance adjustment apparatus according to claim 1, wherein the subject brightness calculation unit calculates the subject brightness using a brightness signal for each of the divided regions and exposure information at the time of shooting the subject.   3. The white balance adjustment device according to claim 2, wherein the color information and the luminance signal for each divided region are generated by performing multiplication of a predetermined white balance coefficient or predetermined linear matrix calculation.   4. The white balance according to claim 1, wherein the light source estimation unit acquires the light source estimation information using a white detection frame group including a plurality of white detection frames respectively corresponding to a plurality of light sources. Adjustment device.   The white balance adjustment device according to claim 4, wherein at least one of reliability and correction amount is set in the plurality of white detection frames respectively corresponding to the plurality of light sources. The light source estimator is
A plurality of white detection frame groups;
According to subject brightness for each of the divided areas, select one of the plurality of white detection frame groups,
The white balance adjustment device according to claim 4, wherein the light source estimation information is acquired using the selected white detection frame group.   The white balance adjustment apparatus according to claim 6, wherein the plurality of white detection frame groups are different in at least one of an arrangement of the plurality of white detection frames, a reliability set in the white detection frame, and a correction amount.   The white balance adjustment device according to any one of claims 4 to 7, wherein the white detection frame group further includes a detection frame of an object color under a predetermined light source. A photographing unit for photographing the subject based on the light flux that has passed through the photographing optical system;
A white balance adjusting device according to any one of claims 1 to 8,
An imaging apparatus comprising: A white balance adjustment method for adjusting the white balance of an image obtained by photographing a subject,
Dividing an image obtained by photographing a subject into a plurality of divided regions;
Generating color information of a subject for each of the divided areas;
Calculating subject brightness of the subject for each of the divided regions;
Obtaining light source estimation information including at least one of an estimated light source, reliability, or correction amount for each of the divided regions based on color information and subject luminance for each of the divided regions;
Calculating a white balance coefficient based on the obtained light source estimation information;
And adjusting the white balance of an image obtained by photographing the subject using the white balance coefficient.

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