Abstract This paper introduces a parallelizable lossless image compression algorithm designed for three-channel standard images and two-channel pathology images. The proposed algorithm builds on the Quite OK Image Format (QOI) by addressing its limitations in parallelizability and compression efficiency, thereby enhancing both the compression ratio and processing speed. By incorporating image context and optimizing pixel traversal sequences, the algorithm enables effective parallel processing, achieving rapid compression of million-pixel pathology images within milliseconds, and is scalable to larger whole-slide images. It also delivers exceptional performance in terms of both speed and compression ratio for standard images. Additionally, the low complexity lossless compression for images (LOCO-I) context prediction algorithm used in joint photographic experts group lossless standard (JPEG-LS) is parallelized to improve compression efficiency and speed. By implementing full-process parallelization across the entire compression workflow rather than confining parallelization to individual steps, this approach significantly enhances overall time performance.
Ht et al. (Thu,) studied this question.