From Dichromatic to Trichromatic Images: Implications for Image Recovery and Visualization.

This paper explores the possibility of recovering a lost color channel from an RGB image, based on the information present in the remaining two color channels, as well as on a priori knowledge about the statistics of sensor responses in a given environment. Different regression and neural network recovery methods are compared and the results show that even simple linear techniques suffice to obtain a good approximation of the original color channel. Remote sensing and other visualization applications can benefit from these methods. Desaturated colors and skin tones are faithfully restored, which is important for the compression of still images and video signals.