Optimizing the Quantization Parameters of the JPEG Compressor to a High Quality of Fine-Detail Rendition
S.V. Sai · Pattern Recognition and Image Analysis · 2018
This paper describes a new algorithm for adaptive selection of DCT quantization parameters in the JPEG compressor. The quantization parameters are selected by classification of blocks based on the composition of fine details whose contrast exceeds the threshold visual sensitivity. Fine details are identified by an original search and recognition algorithm in the N-CIELAB normalized color space, which allows us to take visual contrast sensitivity into account. A distortion assessment metric and an optimization criterion for quantization of classified blocks to a high visual quality are proposed. A comparative analysis of test images in terms of compression parameters and quality degradation is presented. The new algorithm is experimentally shown to improve the compression of photorealistic images by 30% on average while preserving their high visual quality.