On the Robustness of Diffusion-Based Image Compression to Bit-Flip Errors

TL;DR

This paper demonstrates that diffusion-based image compression methods, especially those using Reverse Channel Coding, are significantly more robust to bit-flip errors than traditional codecs, with improved variants enhancing resilience.

Contribution

The study introduces a more robust Turbo-DDCM variant and highlights the superior robustness of RCC-based diffusion compressors against bit errors.

Findings

Diffusion-based compressors outperform classical codecs in robustness to bit flips.

A new Turbo-DDCM variant significantly enhances error resilience.

RCC-based compression reduces the need for error-correcting codes in noisy settings.

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.