CVOct 16, 2023
Distribution prediction for image compression: An experimental re-compressor for JPEG images
arXiv:2310.10517v1h-index: 3
Originality Synthesis-oriented
AI Analysis
This addresses the need for better compression in image storage and transmission, but appears incremental as it builds on existing JPEG methods.
The paper tackles the problem of losslessly re-compressing JPEG images by partially decoding quantized DCT coefficients and re-compressing them more effectively, resulting in improved compression efficiency.
We propose a new scheme to re-compress JPEG images in a lossless way. Using a JPEG image as an input the algorithm partially decodes the signal to obtain quantized DCT coefficients and then re-compress them in a more effective way.