Adjust color balance of RGB image with chromatic adaptation
B = chromadapt(A,illuminant)
B = chromadapt(A,illuminant,Name,Value)
Read an image with a strong yellow color cast. Display the image, specifying an optional magnification to shrink the size of the displayed image.
A = imread('hallway.jpg'); figure imshow(A,'InitialMagnification',25) title('Original Image')
Pick a pixel in the image that should look white or gray, such as a point on a pillar. Do not pick a saturated pixel, such as a point on the ceiling light.
x = 2800; y = 1000; gray_val = [A(y,x,1) A(y,x,2) A(y,x,3)];
Use the selected color as reference for the scene illumination, and correct the white balance of the image.
B = chromadapt(A,gray_val);
Display the corrected image, setting an optional initial magnification.
figure imshow(B,'InitialMagnification',25) title('White-Balanced Image')
The pillars are now white as expected, and the rest of the image has no yellow tint.
Open an image file containing minimally processed linear RGB intensities.
A = imread('foosballraw.tiff');
The image data is the raw sensor data after correcting the black level and scaling to 16 bits per pixel. Interpolate the intensities to reconstruct color. The color filter array pattern is RGGB.
A = demosaic(A,'rggb');
Display the image. Because the image is in linear RGB color space, apply gamma correction so the image appears correctly on the screen. To shrink the image so that it appears fully on the screen, set the optional initial magnification to a value less than 100
A_sRGB = lin2rgb(A); figure imshow(A_sRGB,'InitialMagnification',25) title('Original Image')
The image has a ColorChecker chart in the scene. To get the color of the ambient light, pick a pixel on one of the neutral patches of the chart.
x = 1510; y = 1250; light_color = [A(y,x,1) A(y,x,2) A(y,x,3)]
light_color = 1x3 uint16 row vector 7361 14968 10258
The intensity of the red channel is lower than the intensity of the other two channels, which indicates the light is bluish green.
Balance the color channels of the image. Use the
'ColorSpace' option to specify that the image and the illuminant are expressed in linear RGB.
B = chromadapt(A,light_color,'ColorSpace','linear-rgb');
Display the corrected image, applying gamma correction and setting the initial magnification.
B_sRGB = lin2rgb(B); figure imshow(B_sRGB,'InitialMagnification',25) title('White-Balanced Image')
Confirm that the gray patch has been color balanced.
patch_color = [B(y,x,1) B(y,x,2) B(y,x,3)]
patch_color = 1x3 uint16 row vector 13010 13010 13010
The three color channels in the color-balanced gray patch have similar intensities, as expected.
A— Input RGB image
Input RGB image, specified as a real, nonsparse, m-by-n-by-3 array.
illuminant— Scene illuminant
Scene illuminant, specified as a real, nonempty, 3-element vector. The
illuminant must be in the same color space as the input image,
comma-separated pairs of
the argument name and
Value is the corresponding value.
Name must appear inside quotes. You can specify several name and value
pair arguments in any order as
I2 = chromadapt(I,uint8([22 97 118]),'ColorSpace','linear-rgb')adjusts the color balance of an image,
I, in linear RGB color space.
'ColorSpace'— Color space
Color space of the input image and illuminant, specified as the
comma-separated pair consisting of
'linear-rgb'. Use the
'linear-rgb' option to adjust the color balance
of an RGB image whose intensities are linear.
'Method'— Chromatic adaptation method
Chromatic adaptation method used to scale the RGB values in
A, specified as the comma-separated pair
'Method' and one of:
'bradford'—Scale using the Bradford
cone response model
'vonkries'—Scale using the von Kries
cone response model
'simple'—Scale using the
 Lindbloom, Bruce. Chromatic Adaptation. http://www.brucelindbloom.com/index.html?Eqn_ChromAdapt.html.