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. This way, only a reduced number of parameters is required for coding the color information. Furthermore, since this correlation is in particular high locally, the image is first sub-divided into regions. 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.
Progressive image coding using regional color correlation
01.01.2003
508748 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Progressive Image Coding using Regional Color Correlation
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