A Rate-Distortion-Classification Approach for Lossy Image Compression

arXiv:2405.03500v1 Announce Type: cross
Abstract: In lossy image compression, the objective is to achieve minimal signal distortion while compressing images to a specified bit rate. The increasing demand for visual analysis applications, particularly in classification tasks, has emphasized the significance of considering semantic distortion in compressed images. To bridge the gap between image compression and visual analysis, we propose a Rate-Distortion-Classification (RDC) model for lossy image compression, offering a unified framework to optimize the trade-off between rate, distortion, and classification …

abstract analysis applications arxiv bridge classification compression cs.ai cs.cv cs.it cs.mm demand gap image images math.it rate semantic signal significance tasks type visual while