Revisiting SVD and Wavelet Difference Reduction for Lossy Image Compression: A Reproducibility Study

TL;DR

This study independently reproduces a lossy image compression method combining SVD and WDR, revealing it does not outperform JPEG2000 as claimed, and emphasizes the importance of detailed implementation for reproducibility.

Contribution

The paper provides a detailed reproducibility analysis of the SVD+WDR compression technique, clarifying ambiguities and assessing its actual performance compared to established methods.

Findings

SVD+WDR does not consistently outperform JPEG2000 in PSNR.

Partial SSIM improvements are observed over JPEG2000.

Implementation ambiguities significantly affect reproducibility and results.

Abstract

This work presents an independent reproducibility study of a lossy image compression technique that integrates singular value decomposition (SVD) and wavelet difference reduction (WDR). The original paper claims that combining SVD and WDR yields better visual quality and higher compression ratios than JPEG2000 and standalone WDR. I re-implemented the proposed method, carefully examined missing implementation details, and replicated the original experiments as closely as possible. I then conducted additional experiments on new images and evaluated performance using PSNR and SSIM. In contrast to the original claims, my results indicate that the SVD+WDR technique generally does not surpass JPEG2000 or WDR in terms of PSNR, and only partially improves SSIM relative to JPEG2000. The study highlights ambiguities in the original description (e.g., quantization and threshold initialization) and illustrates how such gaps can significantly impact reproducibility and reported performance.