Hybrid image compression based on polynomial and block truncation coding

In this paper, a simple hybrid lossy image compression system is introduced; it is based on a combination of two techniques that exploits the spatial domain efficiently of linear polynomial approximation model to decompose image signal followed by block truncation coding of two-level quantizer on the residue part of the image, which represents the error caused by applying polynomial approximation. Then, the compressed information encoded using a simple run length coding and Huffman coding techniques. The test results shown in this paper are promising in terms of high compression rate achieved due to integrates the flexibility of polynomial model in overcoming the limitations of extra overhead information required compared to traditional predictive, along with effectiveness of block truncation coding as a 1-bit quantizer moments preserving.