Hierarchical lossless color image coding method using cellular neural networks based predictors

Abstract

This paper proposes the hierarchical lossless color image coding method using CeNNs (cellular neural networks) based predictors. CeNNs are inherently only processing grayscale images, although color image compression utilizes correlations within the RGB color space. To deal with this problem, YCoCg-R color space with low color correlation is employed. The histogram packing technique is also introduced to suppress the expansion of the dynamic range of the chroma. Experimental results confirmed that the proposed method has better coding performance than the conventional method. Compared to FLIF (free lossless image format), the proposed method reduces the bit rate by 8.2%.