Abstract
The conventional multiple component image compression approach separates the input image into several components, each of which is predicted and encoded independently. This approach creates redundancy because the prediction methods as well as the residual subcomponents must be transmitted. In this paper, we propose a new multiple-component predictive coding framework. First, we separate the reconstructed image into several subcomponents. Then, we use the previously encoded subcomponent to predict the current block, and then combine the prediction residuals of each subcomponent. To separate an image into multiple subcomponents, we designed a fast operator-based image separation algorithm. The numerical results demonstrate that the algorithm outperforms the H.264/AVC intra-frame prediction algorithm and the JPEG2000 algorithm on images with ample textures.
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