A Hardware-Oriented Image Compression Algorithm Based on BTC and YEF Color Space

This paper proposes a new compression algorithm based on color sampling and Block Truncation Coding (BTC). It is composed of several steps; color sampling; BTC parameter training; threshold selection; sub-sampling; prediction and quantization; and Huffman coding. The color sampling was applied using YEF color space which reduced 34% storage. The subsequent sub-sampling; quantization table prediction; and Huffman coding further increase compression rates. In addition; the BTC parameter training step finds the best reconstruction value for each 4*4 block and bitmap threshold value to improve the image quality. Compared with previously studies; the proposed algorithm shows a better average compression rate