Lossless Image Coding Using Non-MMSE Algorithms to Calculate Linear Prediction Coefficients

Entropy (Basel). 2023 Jan 12;25(1):156. doi: 10.3390/e25010156.

Abstract

This paper presents a lossless image compression method with a fast decoding time and flexible adjustment of coder parameters affecting its implementation complexity. A comparison of several approaches for computing non-MMSE prediction coefficients with different levels of complexity was made. The data modeling stage of the proposed codec was based on linear (calculated by the non-MMSE method) and non-linear (complemented by a context-dependent constant component removal block) predictions. Prediction error coding uses a two-stage compression: an adaptive Golomb code and a binary arithmetic code. The proposed solution results in 30% shorter decoding times and a lower bit average than competing solutions (by 7.9% relative to the popular JPEG-LS codec).

Keywords: entropy coding; linear prediction; lossless image coding.

Grants and funding

This research received no external funding.