Symbol mapping and context filtering for lossless image compression

Key building blocks of lossless image compression algorithms include adaptive prediction, context-based error feedback and adaptive entropy coding. This paper presents a new alogrithm which includes two other building blocks - symbol mapping and context filtering. Experimental results show that the compression performance of the proposed algorithm is very close to that of CALIC and is better than that of LOGO and S+P. Experimental results also show that symbol mapping and context filtering are promising tools for lossless image compression.