PatchSVD: A Non-uniform SVD-based Image Compression Algorithm

TL;DR

PatchSVD is a new region-based lossy image compression method utilizing SVD, which outperforms traditional SVD and JPEG in quality metrics and produces more desirable artifacts in certain cases.

Contribution

The paper introduces PatchSVD, a novel non-uniform SVD-based image compression algorithm that improves compression quality and artifact characteristics over existing methods.

Findings

PatchSVD outperforms traditional SVD-based compression on key metrics.

PatchSVD produces more preferable artifacts in some cases compared to JPEG.

Experimental results validate the effectiveness of PatchSVD.

Abstract

Storing data is particularly a challenge when dealing with image data which often involves large file sizes due to the high resolution and complexity of images. Efficient image compression algorithms are crucial to better manage data storage costs. In this paper, we propose a novel region-based lossy image compression technique, called PatchSVD, based on the Singular Value Decomposition (SVD) algorithm. We show through experiments that PatchSVD outperforms SVD-based image compression with respect to three popular image compression metrics. Moreover, we compare PatchSVD compression artifacts with those of Joint Photographic Experts Group (JPEG) and SVD-based image compression and illustrate some cases where PatchSVD compression artifacts are preferable compared to JPEG and SVD artifacts.