Bit rate reduction techniques for absolute moment block truncation coding

Block Truncation Coding uses a two-level moment preserving quantizer that a dapts to local properties of the images. It has the features of low computa tion load and low memory requirement while its bit rate is only 2.0 bits pe r pixel. A more efficient algorithm, the absolute moment ETC (AMBTC) has be en extensively used in the field of signal compression because of its simpl e; computation and better MSE performance. We propose postprocessing method s to further reduce the entropy of two output data of AMBTC, including the bit map and two quantization data (a, b). A block of a 2x4 bit map is packa ged into a byte-oriented symbol. The entropy can be reduced from 0.965 bpp to 0.917 bpp on average for our test images. The two subimages of quantizat ion data (a, b) are postprocessed by the Peano Scan. This postprocess can f urther reduce differential entropy about 0.4 bit for a 4x4 block. By applyi ng arithmetic coding, the total bit reduction is about 0.3 similar to 0.4 b pp. The bit rate can reach 1.6 similar to 1.7 bpp with the same quality as traditional AMBTC.