Medical Image Compression Using a Novel Embedded Set Partitioning Significant and Zero Block Coding

Lossless compression with progressive transmission is playing a key role in telemedicine applications. The proposed lossless embedded progressive region based significant and zero block coding uses a recursive set partitioning procedure to sort subsets of wavelet coefficients by maximum magnitude with respect to thresholds that are integer powers of two. It exploits two fundamental characteristics of a wavelet transform – the well defined hierarchical structure and energy clustering in transform domain. The proposed low complexity coder is rooted from Set Partitioning Embedded Block (SPECK) and it is a distortion scalable coder which achieves excellent coding performance. Extensive experiments have verified that the proposed coder is competitive with other state of the coders such as set partitioning in hierarchical trees, SPECK, JPEG2000 on compression performance and computational complexity for standard test images.