In this paper, we study a real-world JPEG image restoration problem with bit errors on the encrypted bitstream. The bit errors bring unpredictable color casts and block shifts on decoded image contents, which cannot be resolved by existing image restoration methods mainly relying on pre-defined degradation models in the pixel domain. To address these challenges, we propose a robust JPEG decoder, followed by a two-stage compensation and alignment framework to restore bitstream-corrupted JPEG images. Specifically, the robust JPEG decoder adopts an error-resilient mechanism to decode the corrupted JPEG bitstream. The two-stage framework is composed of the self-compensation and alignment (SCA) stage and the guided-compensation and alignment (GCA) stage. The SCA adaptively performs block-wise image color compensation and alignment based on the estimated color and block offsets via image content similarity. The GCA leverages the extracted low-resolution thumbnail from the JPEG header to guide full-resolution pixel-wise image restoration in a coarse-to-fine manner. It is achieved by a coarse-guided pix2pix network and a refine-guided bi-directional Laplacian pyramid fusion network. We conduct experiments on three benchmarks with varying degrees of bit error rates. Experimental results and ablation studies demonstrate the superiority of our proposed method. The code will be released at https://github.com/wenyang001/Two-ACIR.

翻译：本文研究真实场景下加密比特流存在比特错误的JPEG图像修复问题。比特错误会导致解码图像内容出现不可预测的色彩偏移和块位移，现有主要依赖像素域预定义退化模型的图像修复方法无法解决这些问题。为应对这些挑战，我们提出一种鲁棒JPEG解码器，并随后采用两阶段补偿与对齐框架来修复比特流损坏的JPEG图像。具体而言，鲁棒JPEG解码器采用容错机制解码损坏的JPEG比特流。两阶段框架由自补偿与对齐（SCA）阶段和引导补偿与对齐（GCA）阶段组成。SCA阶段通过图像内容相似性估计色彩与块偏移，自适应执行块级图像色彩补偿与对齐。GCA阶段利用从JPEG头部提取的低分辨率缩略图，以由粗到细的方式引导全分辨率逐像素图像修复，该过程通过粗引导pix2pix网络与细化引导双向拉普拉斯金字塔融合网络实现。我们在三种不同比特错误率基准上开展实验，实验结果与消融研究证明了所提方法的优越性。代码将发布于https://github.com/wenyang001/Two-ACIR。