Skipping Selected Steps of DWT Computation in Lossless JPEG 2000 for Improved Bitrates

• Published in: PloS one Vol. 11; no. 12; p. e0168704
• Main Author: Starosolski, Roman
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 22.12.2016; Public Library of Science (PLoS)
• Subjects: Algorithms; Coding standards; Compression; Compression tests; Computation; Computer and Information Sciences; Computer Simulation; Data compression; Data Compression - methods; Data Interpretation, Statistical; Decomposition; Diagnostic Imaging - methods; Discrete Wavelet Transform; Efficiency; Engineering and Technology; Entropy; Heuristic; Humans; Image coding; Image compression; Image Enhancement; Image Interpretation, Computer-Assisted - methods; Information technology; JPEG encoders-decoders; Lossless; Medicine and Health Sciences; Noise reduction; Numerical Analysis, Computer-Assisted; Physical Sciences; Research and Analysis Methods; Time compression; Wavelet Analysis; Wavelet transforms
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0168704

In order to improve bitrates of lossless JPEG 2000, we propose to modify the discrete wavelet transform (DWT) by skipping selected steps of its computation. We employ a heuristic to construct the skipped steps DWT (SS-DWT) in an image-adaptive way and define fixed SS-DWT variants. For a large and diverse set of images, we find that SS-DWT significantly improves bitrates of non-photographic images. From a practical standpoint, the most interesting results are obtained by applying entropy estimation of coding effects for selecting among the fixed SS-DWT variants. This way we get the compression scheme that, as opposed to the general SS-DWT case, is compliant with the JPEG 2000 part 2 standard. It provides average bitrate improvement of roughly 5% for the entire test-set, whereas the overall compression time becomes only 3% greater than that of the unmodified JPEG 2000. Bitrates of photographic and non-photographic images are improved by roughly 0.5% and 14%, respectively. At a significantly increased cost of exploiting a heuristic, selecting the steps to be skipped based on the actual bitrate instead of an estimated one, and by applying reversible denoising and lifting steps to SS-DWT, we have attained greater bitrate improvements of up to about 17.5% for non-photographic images.