Revisiting SVD and Wavelet Difference Reduction for Lossy Image Compression: A Reproducibility Study
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908695481286656 |
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| author | Makarova, Alena |
| author_facet | Makarova, Alena |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_06221 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Revisiting SVD and Wavelet Difference Reduction for Lossy Image Compression: A Reproducibility Study Makarova, Alena Computer Vision and Pattern Recognition I.4.2; I.2.10 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. |
| title | Revisiting SVD and Wavelet Difference Reduction for Lossy Image Compression: A Reproducibility Study |
| topic | Computer Vision and Pattern Recognition I.4.2; I.2.10 |
| url | https://arxiv.org/abs/2512.06221 |