Efficient and simple scalable image compression algorithms

Most wavelet-based scalable image compression algorithms are optimized for performance only, i.e., they try to produce a compressed bit-stream that gives the best image quality for the selected bit-rate. Unfortunately, the optimization of the coding method may result in a bit-stream that cannot be rearranged easily to support resolution scalability. This paper proposes two algorithms. The first algorithm produces a rate scalable bit-stream that is optimized for performance and scalability. That is, it has good performance and at the same time it produces bit-stream that can be easily rearranged to become highly (rate and resolution) scalable. To this end, the algorithm combines the low complexity and rate scalability features of the set partitioning coding approach, and it exploits the resolution scalability characteristics of the block-based systems. The second algorithm upgrades the first algorithm to produce a highly scalable bit-stream by only arranging and identifying the different resolutions within the bit-stream. (C) 2019 The Author. Published by Elsevier B.V. on behalf of Faculty of Engineering, Ain Shams University.