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.
Abstract (translated)
这项工作提出了一种对一种结合奇异值分解（SVD）和小波差分减少（WDR）的有损图像压缩技术进行独立再现性研究。原论文声称，将SVD与WDR相结合能够比JPEG2000和单独使用WDR提供更好的视觉质量和更高的压缩比率。我重新实现了所提出的方法，仔细审查了缺失的实现细节，并尽可能地复制了原始实验。然后，我在新的图像上进行了额外的实验，并利用PSNR（峰值信噪比）和SSIM（结构相似性指数）对性能进行了评估。 与原论文中的说法相反，我的结果表明SVD+WDR技术在PSNR方面通常不如JPEG2000或WDR，在SSIM方面的改善也仅部分优于JPEG2000。这项研究强调了原始描述中存在的模糊之处（例如量化和阈值初始化），并展示了这些缺口如何显著影响再现性和报告的性能。
URL
https://arxiv.org/abs/2512.06221
