A Visual Model Weighted Cosine Transform for Image Compression and Quality Assessment

Utilizing a cosine transform in image compression has several recognized performance benefits, resulting in the ability to attain large compression ratios with small quality loss. Also, incorporation of a model of the human visual system into an image compression or quality assessment technique intuitively should (and has often proven to) improve performance. Clearly, then, it should prove highly beneficial to combine the image cosine transform with a visual model. In the past, combining these two has been hindered by a fundamental problem resulting from the scene alteration that is necessary for proper cosine transform utilization. A new analytical solution to this problem, taking the form of a straightforward multiplicative weighting function, is developed in this paper. This solution is readily applicable to image compression and quality assessment in conjunction with a visual model and the image cosine transform. In the development, relevant aspects of a human visual system model are discussed, and a refined version of the mean square error quality assessment measure is given which should increase this measure's utility.