JP2000278708A - Digital camera - Google Patents

Abstract

PROBLEM TO BE SOLVED: To properly adjust white balance even when a color of an object is in dispersion by calculating an optimum gain based on a principal color component. SOLUTION: A CPU 34 receives picture data corresponding to an object image from a RAM 20 to specify a principal color component of the object image based on the picture data. Then an optimum gain is calculated on the specified principal color component and set to amplifiers 26, 28. Since the optimum gain is calculated based on the principal color component, even when a color of the object is in dispersion, white balance can properly be adjusted.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a white balance adjustment circuit, and more particularly to, for example, a digital camera, which evaluates the color of a subject from an image signal color information signal of the subject image.
The present invention relates to a white balance adjustment circuit that adjusts a white balance based on a color evaluation value.

[0002]

2. Description of the Related Art In a conventional white balance adjustment circuit of this type, a plurality of color evaluation values within a pull-in range are detected.
The white balance has been adjusted so that the average value of the detected color evaluation values converges on the intersection of the RY axis and the BY axis.

[0003]

However, such a conventional technique has a problem that the white balance adjustment becomes insufficient when the evaluation values of the respective colors vary. That is, for example, when the color evaluation values are distributed as shown in FIG.
The amplifier gain is determined so that the average of the color evaluation values moves to the intersection of the RY axis and the BY axis shown in FIG. For this reason, sufficient white balance adjustment has not been performed on the warm color that the subject mainly takes on.

[0004] Therefore, a main object of the present invention is to provide a digital camera capable of appropriately adjusting the white balance even when the colors of the subject vary.

[0005]

SUMMARY OF THE INVENTION The present invention provides a photographing means for photographing a subject image, a specifying means for specifying a main color component of the subject image, a calculating means for calculating an optimum gain based on the main color component, and an optimum gain. Is a digital camera including an adjusting unit that adjusts a white balance of a subject image according to the following.

[0006]

When a subject image is photographed by the photographing means, the specifying means specifies a main color component of the subject image. The calculating means calculates the optimum gain based on the main color component, and the adjusting means adjusts the white balance of the subject image according to the calculated optimum gain.

[0007] In one aspect of the present invention, the application means is provided with the first means.
Gain is applied to the image signal. The generation unit generates a plurality of color components based on the image signal having the first gain, and the detection unit detects a first color component included in the first range from the generated plurality of color components. The first updating means updates the first gain based on the first color component detected in this manner. The first color component detected by the detecting unit after the first gain is updated by the first updating unit is the main color component.

[0008] The generation means generates a plurality of color components by integrating the image signal having the first gain for each predetermined portion and for the same color.

In one embodiment of the present invention, the second gain calculating means calculates the second gain based on the main color component. The weighting means obtains an optimum gain by performing predetermined weighting on the second gain and the first gain.

In another embodiment of the present invention, the second detecting means detects a second color component included in the second range from the main color components. Further, the ratio of the second color component to the main color component is calculated by the ratio calculation means. The weighting means performs the above-described weighting according to the ratio calculated as described above.

[0011]

According to the present invention, the optimum gain is calculated based on the main color component of the subject image, and the white balance of the subject image is adjusted according to the calculated optimum gain. The white balance can be adjusted appropriately even when there is a color.

The above objects, other objects, features and advantages of the present invention will become more apparent from the following detailed description of embodiments with reference to the drawings.

[0013]

Referring to FIG. 1, a digital camera 10 of this embodiment includes an optical lens 12. This optical lens 1
The object image incident through 2 is irradiated on the CCD imager 16 via the complementary color filter 14. The complementary color filter 14 includes Ye, Cy, Mg, and G as shown in FIG.
And one filter element corresponds to one pixel. Therefore, each pixel signal output from the CCD imager 16 has only one color of Ye, Cy, Mg, and G.

Such a pixel signal is supplied to the A / D converter 18.
Is converted into a digital signal, that is, pixel data by
The pixel data is stored in the RAM 2 by the memory controller 22.
0 is temporarily stored.

In the camera mode for displaying a moving image of a subject on the monitor 40 in real time, the memory controller 2
2 executes writing data to the RAM 20 and reading data from the RAM 20 in parallel. Therefore, A
The image data generated by the / D converter 18 is read from the RAM 20 with a delay of one frame. Signal processing circuit 24
Generates RGB data from input pixel data. The pixel data has a color of Ye, Cy, Mg, or G as described above. Therefore, the signal processing circuit 24 performs a matrix operation on such complementary color-based pixel data to generate primary color-based pixel data in which each pixel has R, G, and B colors.

The R data is multiplied by α by the amplifier 26, and the B data is multiplied by β by the amplifier 28. That is, the gain α is given to the R data, and the gain β is given to the B data. On the other hand, no gain is given to the G data. R 'data and B' output from amplifiers 26 and 28, respectively.
The data and the G data output from the signal processing circuit 24 are then subjected to a matrix operation, whereby luminance data Y and color difference data R'-Y and B'-Y are generated. These data are then transmitted to the signal processing circuit 36.
Is output to the monitor 40 through a predetermined process. As a result, a through image is displayed on the monitor screen.

The R ′ data, G data and B ′ data are also input to the integration circuit 32. The screen is divided into 16 in the horizontal and vertical directions as shown in FIG. 3, and 256 divided areas are formed on the screen. The integration circuit 32
The R ′ data, G data and B ′ data are integrated for each of such divided areas and for each of the same colors. Therefore, 256 integrated values IR ', 256 integrated values IG, and 256 integrated values IB' are obtained in one frame period. That is, 256 color evaluation values corresponding to each divided area are obtained. The CPU 34 controls the gains α and β of the amplifiers 26 and 28 based on these color evaluation values. As a result, a through image in which the white balance is appropriately adjusted is displayed on the monitor.

When the operator operates the shutter button 42, the signal processing circuit 24 is disabled. The memory controller 22 stops the data writing operation when the pixel data output from the CCD imager 16 is written into the RAM 20 in response to the operation of the shutter button 42. However, the reading operation is continued. C
The PU 34 takes in the pixel data read from the RAM 20, and sets the optimum gains α and β in the amplifiers 26 and 28 according to the flowcharts shown in FIGS.
That is, the white balance of the subject image (still image) photographed in response to the operation of the shutter button 42 is adjusted according to the flowcharts shown in FIGS. When the white balance adjustment is completed, the signal processing circuit 24 is activated again. R
The pixel data read from the AM 20 is transmitted to the signal processing circuit 2
4 for RGB conversion, and then R data and B
Optimal gains α and β are given to the data. Gain α
The R ′ data and B ′ data to which β and β have been given and the G data output from the signal processing circuit 24 are thereafter recorded in the memory card 38 through the processing of the signal processing circuit 36.

Referring to FIGS. 4 and 5, CPU 34 first resets counter 34d in step S1. In step S3, the pixel data of the complementary color system read from the RAM 20 is subjected to RGB conversion in accordance with Equation 1, and pixel data of the primary color system in which each pixel has all the colors of R, G and B is generated.

[0020]

(Equation 1)

The CPU 34 subsequently proceeds to step S5,
R data, G data and B generated in step S3
Data is integrated for the same color and for each divided area shown in FIG. That is, the same processing as that of the integration circuit 32 described above is executed by software. As a result, 256 integrated values IR (x), 256 integrated values IG (x), and 256 integrated values IB (x) are obtained. That is, 256 color evaluation values corresponding to each divided area are obtained. Note that “x” indicates the number of each divided area, and takes any value from 0 to 255.

In step S7, the integrated value IR is calculated according to equation (2).
(X) is multiplied by the gain α1.
Is multiplied by the gain β1 according to the following equation.
Gain α used in first steps S7 and S9
1 and β1 are stored in the memory 34c in advance, and 5
When a subject having a color temperature of 100K (reference color temperature) is photographed, the white balance is appropriately adjusted. Since there is an error in the characteristics of each manufactured CCD imager, if the integrated value IR (x) and the integrated value IB (x) are used as they are, the gains finally set in the amplifiers 26 and 28 are shifted. . Therefore, at the time of manufacturing each digital camera, the gains α1 and β1 are individually calculated and written into the memory 34c. By multiplying the integrated value IR (x) and the integrated value IB (x) by such a gain, the integrated values IR ′ (x), IG (x), and IB ′ (x) calculated when the same subject is photographed. )
Will be the same for each digital camera.

[0023]

(Equation 2)

[0024]

(Equation 3)

Subsequently, in step S11, the CPU 34 calculates an integrated value IR'-Y (x) and an integrated value IB'-Y (x) from the integrated value IR '(x) and the integrated value IB' (x). The calculated integrated values IR'-Y (x) and IB '
-Y (x) is equal to the value obtained by integrating the color difference data R'-Y and B'-Y for each divided area. Such integrated values IR'-Y (x) and IB'-Y (x) are also color evaluation values in each divided area.

The CPU 34 thereafter proceeds to step S13, and detects a weighting coefficient γ (x) corresponding to the color evaluation value obtained in step S11 from the weighting table 34a shown in FIG. Weighting coefficients “0” and “1” are stored in the weighting table 34a, and each weighting coefficient corresponds to the graph shown in FIG. In other words, the BY axis and the RY axis are each divided into 17, and each quadrant divided by the BY axis and the RY axis is divided into 64. Then, the above-mentioned weighting coefficients are assigned to the 290 areas thus formed one by one. Among these, the range to which the weighting coefficient “1” is assigned forms the first pull-in range. In other words, all the weighting factors within the first pull-in range are “1”, but all the weighting factors outside the first pull-in range are “0”.

In step S13, a weighting coefficient γ (x) of each divided area shown in FIG. 3 is detected from such a weighting table 34a.

Subsequently, the CPU 34 calculates Equations 4 and 5 in Steps S15 and S17, respectively, and calculates the integrated values IR (x), IG (x) and IB (x) obtained in Step S5 and Step S13. The gain α2 and the gain β2 are calculated based on the detected weighting coefficient γ (x).

[0029]

(Equation 4)

[0030]

(Equation 5)

Since the weighting coefficient γ (x) has only “0” or “1”, by multiplying γ (x) by IG (x) and IR (x), the color evaluation value falls within the first pull-in range. Values IG (x) and IR of the divided areas in
Only (x) is valid. In Equation 4, the sum of such effective integrated values IG (x) and the sum of effective integrated values IR (x) are obtained, and the amount of deviation between these sums is obtained. Number 5
Also, only the divided areas whose color evaluation values are within the first pull-in range are valid, and the shift amount of the sum of the integrated values IG (x) and the sum of the integrated values IB (x) in the effective divided areas is obtained. The gain α thus obtained
2 and β2 take values such that the average of the color evaluation values included in the first pull-in range converges to the intersection of the RY axis and the BY axis.

Subsequently, the CPU 34 increments the counter 34d in a step S19, and determines whether or not the count value of the counter 34d has reached "2" in a step S21. Since the count value is 1 at the first judgment,
The CPU 32 proceeds to step S23, and updates the gains α1 and β1 with the gains α2 and β2 calculated in steps S15 and S17, respectively. Then, the processing of steps S7 to S19 is executed again. Step S
At 7 and S9, the updated gains α1 and β1 are multiplied by the integral values IG (x) and IR (x). 2
Since the count value is 2 at the time of the processing in step S21, the CPU 34 determines YES in step S21, and proceeds to step S25.

In step S25, the first step S
11 based on the color evaluation value obtained by the processing of FIG. 11 and the weighting table 34b.
(X) is detected. FIG. 7 shows the weighting table 34b.
As shown in FIG. 7A, a plurality of weighting factors λ (x) are stored, and these weighting factors λ (x) are associated with the graph shown in FIG. 7B. That is, the graph shown in FIG. 7B is divided into 290 similarly to the above, and “0” or “1” is assigned to each area. this house,
The range to which "1" is assigned forms the second pull-in range. That is, the weighting coefficients in the second pull-in range are all “1”, and the weighting coefficients outside the second pull-in range are all “0”. In step S25, a weighting coefficient corresponding to the color evaluation value of each divided area is detected from such a weighting table 34b. Note that FIG.
7A, the first pull-in range is larger than the second pull-in range.

Thereafter, the CPU 34 calculates Equation 6 in step S27. That is, the number of divided areas whose color evaluation values are included in the second pull-in range is divided by the number of divided areas included in the first pull-in range, and multiplied by “100”. As a result, the ratio of the color evaluation value included in the second pull-in range among the color evaluation values included in the first pull-in range is obtained. This ratio becomes the weighting amount ε.

[0035]

(Equation 6)

In steps S23 and S25, equations (7) and (8) are calculated, and optimum gains α and β actually set in the amplifiers 26 and 28 are obtained. In equation 7, the gain α1 updated in step S23 and the second step S1
5 is weighted according to the weighting amount ε. Similarly, in equation 8, the gain β1 updated in step S23 and the gain β2 calculated in the second step S15 are weighted according to the weighting amount ε.

[0037]

(Equation 7)

[0038]

(Equation 8)

When the optimum gains α and β are calculated by the equations (7) and (8), the CPU 34 sets these gains in the amplifiers 26 and 28 in step S27, and ends the processing.

As described above, first, the gains α1 and β1
Weighting coefficient γ (x) corresponding to the color evaluation value to which is added
Is detected from the weighting table 34a. That is,
The divided area whose weighting coefficient γ (x) is “1” is validated. Next, the gains α2 and β2 are calculated based on the color evaluation values corresponding to the activated divided areas and not provided with the gains α1 and β1.

When the color evaluation values to which the gains α1 and β1 are not added and the color evaluation values to which the gains α1 and β1 are added are distributed as shown in FIG. The gains α2 and β2 obtained in S17 are values such that the average value A of the color evaluation values to which the gains α1 and β1 are added moves to the intersection of the RY axis and the BY axis. That is, the color evaluation value is
The gains α2 and β2 are obtained so as to be distributed at the positions shown in FIG.

When the gains α2 and β2 are obtained, the gains α1 and β1 are updated by these gains, and the same processing as described above is executed again. That is, the weighting coefficient γ (x) corresponding to the color evaluation value having the updated gains α1 and β1 (α2 and β2) is detected,
The divided area whose weighting coefficient γ (x) is “1” is validated. That is, only the divided areas having the warm color evaluation values shown in FIG. 8B are valid. In the second steps S15 and S17, the gains α2 and β2 are updated based on the color evaluation values corresponding to such effective divided areas and not provided with the gains α1 and β1. The updated gains α2 and β2 are values such that the average value of the warm color color evaluation values moves to the intersection of the RY axis and the BY axis.

That is, a subject having a color evaluation value as shown in FIGS. 8A and 8B mainly has a warm color. That is, the main color component of the subject is a warm color. Therefore, in the second step S13, the divided area having the warm color-based color evaluation value is validated, and the second step S1 is performed.
In steps 5 and S17, the gains α2 and β2 are determined so that the average of such color evaluation values converges on the intersection of the RY axis and the BY axis.

Subsequently, for the color evaluation values having the gains α2 and β2 calculated at the first time, the ratio ε of the color evaluation values included in the second pull-in range among the color evaluation values included in the first pull-in range. Is calculated. The gain α2 (α1) calculated for the first time and the gain α2 calculated for the second time are weighted according to such a ratio ε. The gain β2 (β1) calculated for the first time and the gain β2 calculated for the second time are also weighted in the same manner. In this way, the amplifiers 26 and 28 are actually
Are determined.

The gains α2 and β2 calculated for the first time
When the color evaluation value having the “?” Straddles the second pull-in range as shown in FIG. The second gains α2 and β2 are distributed between the assigned color evaluation values.

As shown in FIG. 8A, when a subject image in which color evaluation values are distributed is photographed by a conventional digital camera,
The gains α and β are such that the average value A is the RY axis and the BY
The value was set to move to the intersection of the axes. For this reason, sufficient white balance adjustment has not been performed on the warm-colored colors in which the subject image is mainly taken. In contrast, in this embodiment, the gain is calculated by focusing only on the main color components of the subject image, and the white balance is adjusted. That is, the optimum gain is calculated based on the main color component of the subject image, and the optimum gain is set in the amplifier. Therefore, even when the colors of the subject vary, the white balance can be appropriately adjusted.

[Brief description of the drawings]

FIG. 1 is a block diagram showing one embodiment of the present invention.

FIG. 2 is an illustrative view showing a color filter;

FIG. 3 is an illustrative view showing one example of a subject image;

FIG. 4 is a flowchart showing a part of the operation of the embodiment in FIG. 1;

FIG. 5 is a flowchart showing another portion of the operation of the embodiment in FIG. 1;

FIG. 6A is an illustrative view showing one example of a weighting coefficient corresponding to each color evaluation value, and FIG. 6B is a graph showing hue and color density;

FIG. 7A is an illustrative view showing another example of a weighting coefficient corresponding to each color evaluation value, and FIG. 7B is a graph showing hue and color density;

FIG. 8 is an illustrative view showing one portion of an operation of the embodiment in FIG. 1;

FIG. 9 is an illustrative view showing another portion of the operation of the embodiment in FIG. 1;

FIG. 10 is an illustrative view showing one portion of a conventional operation;

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 10 ... Digital camera 16 ... CCD imager 20 ... RAM 24 ... Signal processing circuit 26,28 ... Amplifier 34 ... CPU

Claims (7)

[Claims] A photographing unit for photographing a subject image; a specifying unit for specifying a main color component of the subject image; a calculating unit for calculating an optimum gain based on the main color component; A digital camera comprising an adjusting unit for adjusting a white balance. 2. The image processing apparatus according to claim 1, wherein the specifying unit includes: an applying unit that applies a first gain to the image signal; a generating unit that generates a plurality of color components based on the image signal having the first gain; 2. The digital camera according to claim 1, further comprising: first detection means for detecting a first color component included in a first range, and first updating means for updating the first gain based on the first color component. 3. The digital camera according to claim 2, wherein said generation means generates the plurality of color components by integrating the image signal having the first gain for each predetermined portion and between the same colors. 4. The method according to claim 1, wherein said first gain is updated by said first updating means and said first gain detected by said detecting means is updated.
4. The digital camera according to claim 2, wherein a color component is the main color component. 5. The second gain calculating means for calculating a second gain based on the main color component, and a predetermined weighting applied to the first gain and the second gain to calculate the optimum gain. 5. The digital camera according to claim 2, further comprising a weighting means for determining. 6. A second detecting means for detecting a second color component included in a second range among the main color components, and a ratio calculating means for calculating a ratio of the second color component to the main color component. Furthermore, the weighting means performs weighting according to the ratio,
The digital camera according to claim 5. 7. The digital camera according to claim 6, wherein said second range is smaller than said first range.