Compound images consist of text, graphics and natural images, which present strong anisotropic features. It makes existing image coding standards inefficient on compressing them. To solve the problem, this paper proposes a novel coding scheme based on the H.264 intra-frame coding. Two new intra modes are proposed to better exploit spatial correlations in compound images. The first is residual scalar quantization (RSQ) mode, where intra-predicted residues are directly quantized and entropy coded. The second is base colors and index map (BCIM) mode that can be viewed as an adaptive vector quantization. In this mode, an image block is represented by several representative colors, called as base colors, and an index map to compress. Two new modes as well as previous intra modes in H.264 are selected by the rate-distortion optimization (RDO) method in each block. Experimental results show that the proposed scheme not only improves the coding efficiency even more than 10dB for compound images but also keeps the similar performance as H.264 for natural images.
['Cuiling Lan', 'Feng Wu', 'Guangming Shi']
Compress compound images in H.264/MPEG-4 AVC by fully exploiting spatial correlation