The main goal for this activity is to balance unbalanced images using white patch (WP) and gray world (GW) algorithms. The image is unbalanced if the portions that are supposed to be white do not appear white. Just like the images in Figure 1, the supposedly white portions appear bluish. This means the images are captured using a WB setting not appropriate for the lighting conditions of the room/surroundings.
White patch algorithm divides all RGB values with the RGB values of the supposedly white portions. In doing so, these portions are forced to have a value of 1 producing a true white color. In this case, the bluish color can be thought of as an offset of the white color. Forcing the bluish color to be white allows the rest of the colors to be rendered correctly with respect to the white color. The balanced images using WP algorithm appear darker in Figure 1 (second column) because a constant (< style="text-decoration: underline;">
White patch algorithm divides all RGB values with the RGB values of the supposedly white portions. In doing so, these portions are forced to have a value of 1 producing a true white color. In this case, the bluish color can be thought of as an offset of the white color. Forcing the bluish color to be white allows the rest of the colors to be rendered correctly with respect to the white color. The balanced images using WP algorithm appear darker in Figure 1 (second column) because a constant (< style="text-decoration: underline;">
Figure 1. White balancing of unbalanced images. First column: unbalanced images; second column: using white patch algorithm; third column: using gray world algorithm.
Figure 2. White balancing of unbalanced images. First column: unbalanced images; second column: using white patch algorithm; third column: using gray world algorithm.
Figure 3 below shows the balancing of an image containing only a single hue. The resulting images show that WP algorithm produces better results than GW algorithm. Unlike in the multicolor images (Figures 1 and 2), the single hue introduces a bias in the balancing of the image. The yellowish color in the balanced image of GW algorithm is due to the bias in the red color since the mean of the whole image (mostly red) is used and not just of the white portion.
Figure 3. The white portion inside the black circle is the white patch used.
Figure 3. The white portion inside the black circle is the white patch used.
Figure 4. White balancing of an unbalanced image with single hue. First column: unbalanced images; second column: using gray world algorithm; third column: using white patch algorithm.
For this activity, I would give myself a grade of 10 because I was able to balance the images using both algorithms and explain the results I got. Thank you to Thirdy and all those who lent me their things for the photoshoot.
What white part in figure 3 did you use for the white patch algorithm?
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