Lossless image compression using adaptive predictor symbol mapping and context filtering

Common components in recently published lossless image compression algorithms include adaptive prediction, context-based error feedback and adaptive entropy coding. Each component has a number of building blocks. In this paper, we present a new algorithm which uses three new building blocks: an adaptive predictor, a symbol mapping scheme and a context filtering scheme. Experimental results show that the compression performance of the proposed algorithm is better than those of the three state-of-the-art algorithms: CALIC, HBB and LOGO. Experimental results also show that the proposed new building blocks are promising tools for lossless image compression.