Abstract: Digital images, as an important carrier, have been applied in various fields. The generation of many color images occupies a large amount of storage space and network bandwidth. Therefore, color image compression has become a key technology. Absolute Moment Block Truncation Coding (AMBTC), as one of the classic image compression schemes, has been widely studied. However, in existing related schemes, the visual quality and compression rate of reconstructed images are relatively low. To address this problem, a color image compression method based on multi-grouping absolute moment block truncation coding (MGAMBTC) and sort mapping is proposed. The sort mapping algorithm is proposed by utilizing the feature of multiple quantization levels in MGAMBTC. By reordering the quantization levels and mapping them onto the first few bits of the bitmap, the bitmap is compressed. This scheme achieves higher visual quality of reconstructed images than other schemes at the same bit rate. At the same time, the effectiveness of the sort mapping algorithm is demonstrated in experiments. 

Key words: color image compression, multi-grouping absolute moment block truncation coding, sort mapping, human visual system, Huffman encoding