Multi-Partition Block Truncation Coding for Image Compression

Image compression is used to reduce the size of digital image files in order to lessen the physical storage and transmission bandwidth costs. The main challenge in image compression is reducing the file size while maintaining much of the visual information. In this study, we explore one class of image compression techniques – the Block Truncation Coding (BTC) – and propose a new variant which we refer to as Multi-partition BTC. This variant was implemented and then compared against some of the existing BTC variants by running the algorithms on a standard dataset. The Peak Signal-to-Noise Ratio (PSNR) and the compression ratio for each of the BTC variants were recorded and compared. The results show that the proposed technique yields superior PSNR while maintaining a considerably good compression rate. Moreover, the low computational complexity and fast image encoding of the proposed BTC variant make it viable for real applications.