On the Robustness of Diffusion-Based Image Compression to Bit-Flip Errors
About
Modern image compression methods are typically optimized for the rate--distortion--perception trade-off, whereas their robustness to bit-level corruption is rarely examined. We show that diffusion-based compressors built on the Reverse Channel Coding (RCC) paradigm are substantially more robust to bit flips than classical and learned codecs. We further introduce a more robust variant of Turbo-DDCM that significantly improves robustness while only minimally affecting the rate--distortion--perception trade-off. Our findings suggest that RCC-based compression can yield more resilient compressed representations, potentially reducing reliance on error-correcting codes in highly noisy environments.
Amit Vaisman, Gal Pomerants, Raz Lapid• 2026
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Image Compression | Kodak24 (test) | PSNR24.05 | 8 | |
| Image Compression | DIV2K (val) | PSNR22.03 | 8 | |
| Robust Image Compression | Kodak24 | PSNR22.57 | 8 | |
| Robust Image Compression | DIV2K | PSNR20.74 | 8 |
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