20.500.12556/DKUM-91488 A case study on entropy-aware block-based linear transforms for lossless image compression Data compression algorithms tend to reduce information entropy, which is crucial, especially in the case of images, as they are data intensive. In this regard, lossless image data compression is especially challenging. Many popular lossless compression methods incorporate predictions and various types of pixel transformations, in order to reduce the information entropy of an image. In this paper, a block optimisation programming framework is introduced to support various experiments on raster images, divided into blocks of pixels. Eleven methods were implemented within , including prediction methods, string transformation methods, and inverse distance weighting, as a representative of interpolation methods. Thirty-two different greyscale raster images with varying resolutions and contents were used in the experiments. It was shown that reduces information entropy better than the popular JPEG LS and CALIC predictors. The additional information associated with each block in is then evaluated. It was confirmed that, despite this additional cost, the estimated size in bytes is smaller in comparison to the sizes achieved by the JPEG LS and CALIC predictors. computer science information entropy prediction inverse distance transform string transformations računalništvo entropija stiskanje slik true false true Springer Nature Angleški jezik Slovenski jezik https://www.nature.com/srep/ © The Author(s) 2024 Članek v reviji 2025-01-07 14:01:59 2025-01-07 14:01:59 2026-05-14 03:10:22 0000-00-00 00:00:00 2024 0 0 15 str. let. 14 28 Nov. 2024 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2024-07-27 2024-11-05 2024-11-28 004.9 217965571 10.1038/s41598-024-79038-2 2045-2322 s41598-024-79038-2.pdf s41598-024-79038-2.pdf 1 51E87AFB067021C880E9B5D32E87D844 a4d609088e6982c7ab64b756d79ba8ceafb5641d2255b88cd4d21b558fa417c9 14bae076-4ec5-11f1-a165-00155d0001a1 https://dk.um.si/Dokument.php?lang=slv&id=206084 https://www.nature.com/articles/s41598-024-79038-2#article-info 0 3df2e86f-4ec5-11f1-a165-00155d0001a1 https://dk.um.si/Dokument.php?lang=slv&id=206085 Fakulteta za elektrotehniko, računalništvo in informatiko 0 0 0