Color Image Processing

This activity, we were taught about colors, taking pictures and camera features such as white balancing. White balancing ensures that the captured image is has proper values for white and for all other colors as well.

To achieve white balancing, there are 2 popular algorithms - the White Patch Algorithm and the Gray World algorithms. Their difference is that, normalization factor that fixes the color rendered. The white patch algorithm obtains white values to a white patch in the image while gray world algorithm obtains the mean value of the whole image.

Using images captured at different light sources with different white balance, respective White Patch and Gray World algorithms are shown below.


In White patch algorithm, one will pick the worst ill- white balanced object. Then, the white value of that is used to normalize all the color values for the rest of the pictures of the same illumination.

I noticed that they form kind of SEPIA-ish,...

Using the hues on the otherhand, GW and WP algorithms are also used. And it yielded this result.


With the two algorithms, I think the WP algorithm is better. From the result, there are black points in the GW algorithm. Maybe they are information losses. And I also think that, the Rw Gw Bw obtained in WP is better because you are getting the value of white in the worst white balanced object. Also, Rw, Gw and Bw are values for white. White is the maxima per RGB. It is the most proper to use as normalization factor. Unlike in the GW that the mean is being used as Rw Gw Bw.


I'd grade myself 9/10 for this activity. It is fun though to mess around in white balancing.
Thanks to May Ann for the images. We don't have a proper camera to do capture the image.
Thanks Maam Jing for the input on GW and WP algorithms.