Activity 12: Color Camera Processing

Results:

Images differ depending on the light source it has been captured. Our brain has the capacity to balance an image depending on what it knows to be color white. This process is called white balancing and this algorithm is also used by cameras to correct an image and make it look natural. There are two white balancing algorithms commonly used. First is the white path algorithm wherein you divide the pixel values of the image by the pixel value of the white object. Another is the gray world algorithm wherein you consider the assumption that the world is gray and thus divide the pixel values of the image by the average of all pixel value on the image. Figures below show the process of white balancing images with incorrect white balance settings. All of the images are captured from a flourescent light source and different white balancing settings are used.

Figure 1: Original Image (Cloudy White Balance)[Top], White Patch Algorithm [Middle], Gray World Algorithm [Buttom]

White Patch Algorithm:

Rw = 0.5921569

Gw = 0.6235294

Bw = 0.5333333

Gray World Algorithm:

Rw = 0.3592001

Gw = 0.3325416

Bw = 0.2280096

Figure 2: Original Image (Day Light White Balance)[Top], White Patch Algorithm [Middle], Gray World Algorithm [Buttom]

White Patch Algorithm:

Rw = 0.5058824

Gw = 0.5568627

Bw = 0.5215686

Gray World Algorithm:

Rw = 0.3326466

Gw = 0.3326723

Bw = 0.2590823

Figure 3: Original Image (Fluorescent High White Balance)[Top], White Patch Algorithm [Middle], Gray World Algorithm [Buttom]

White Patch Algorithm:

Rw = 0.5490196

Gw = 0.5333333

Bw = 0.5294118

Gray World Algorithm:

Rw = 0.3809007

Gw = 0.3120621

Bw = 0.2727691

Figure 4: Original Image (Fluorescent White Balance)[Top], White Patch Algorithm [Middle], Gray World Algorithm [Buttom]

White Patch Algorithm:

Rw = 0.5254902

Gw = 0.5647059

Bw = 0.6117647

Gray World Algorithm:

Rw = 0.3553569

Gw = 0.342048

Bw = 0.3251807

Figure 5: Original Image (Tungsten White Balance)[Top], White Patch Algorithm [Middle], Gray World Algorithm [Buttom]

White Patch Algorithm:

Rw = 0.4

Gw = 0.5568627

Bw = 0.7607843

Gray World Algorithm:

Rw = 0.2765657

Gw = 0.3423595

Bw = 0.4473613

In determining which of the two algorithms is better, we take another picture with object with almost the same color. We apply the algorithms and Figure 6 shows the results.

Figure 5: Test Image (Tungsten White Balance)[Top], White Patch Algorithm [Middle], Gray World Algorithm [Buttom]

The white patch algorithms shows a better image quality compared to the gray world algorithm. That is to say even though the white patch algorithm requires the pinpointing of the object that is supposed to be white, the image reconstructed is better. The gray world algorithm on the other hand works best if the image being processed has many colors represented. If this is the case the balancing value represents the average of almost all the colors and thus give a better reconstruction:

References:

[1] M.Soriano,"Activity 12: Color Camera Processing", AP 186, 2010

Self Evaluation: 10