COLOR IMAGE CODING USING REGIONAL CORRELATION 
OF PRIMARY COLORS

Yalon Roterman and Moshe Porat,
Department of Electrical Engineering, 
Technion - Israel Institute of Technology 
Haifa 32000, Israel


Abstract

Most color compression systems reduce the redundancies between the 
RGB color components by transforming the color primaries into a 
decorrelated color space, such as YIQ or YUV. In this paper a different 
compression approach is proposed. Since the high correlation of the 
RGB color channels implicitly suggests a localized functional relation 
between the components, it is used here in an alternative framework, 
by approximating subordinate colors as functions of a base color 
allowing that only a reduced number of parameters is required for 
coding the color information. Furthermore, since this correlation is 
particularly high locally, the image is first sub-divided into regions 
and for each region the correlation is analyzed and exploited separately. 
The size of the encoded regions is gradually reduced to allow 
progressively a more refined description of the transmitted image. 
Compression results of this progressive approach, which could be useful 
for slower communication channels, are presented and compared with 
JPEG as a typical example of the decorrelation approach. Our 
conclusion is that the proposed new approach to progressive image 
coding could be superior to presently available compression techniques.

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Elsevier Image and Vision Computing, Vol. 25, pp. 637-651 (2007).