Abstract
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.
Abstract (translated)
现代图像压缩方法通常针对码率-失真-感知度权衡进行优化，而其对比特级损坏的鲁棒性却很少被考察。我们证明，基于反向信道编码（RCC）范式的扩散压缩器在比特翻转方面比传统及学习型编解码器具有显著更高的鲁棒性。我们还引入了Turbo-DDCM的一个更鲁棒变体，该变体在显著提升鲁棒性的同时，仅对码率-失真-感知度权衡产生极小影响。我们的研究结果表明，基于RCC的压缩能够产生更鲁棒的压缩表示，在高噪声环境中可能减少对纠错码的依赖。
URL
https://arxiv.org/abs/2604.05743
