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In this paper, we study a real-world JPEG image restoration problem with biterrors on the encrypted bitstream. The bit errors bring unpredictable colorcasts and block shifts on decoded image contents, which cannot be resolved byexisting image restoration methods mainly relying on pre-defined degradationmodels in the pixel domain. To address these challenges, we propose a robustJPEG decoder, followed by a two-stage compensation and alignment framework torestore bitstream-corrupted JPEG images. Specifically, the robust JPEG decoderadopts an error-resilient mechanism to decode the corrupted JPEG bitstream. Thetwo-stage framework is composed of the self-compensation and alignment (SCA)stage and the guided-compensation and alignment (GCA) stage. The SCA adaptivelyperforms block-wise image color compensation and alignment based on theestimated color and block offsets via image content similarity. The GCAleverages the extracted low-resolution thumbnail from the JPEG header to guidefull-resolution pixel-wise image restoration in a coarse-to-fine manner. It isachieved by a coarse-guided pix2pix network and a refine-guided bi-directionalLaplacian pyramid fusion network. We conduct experiments on three benchmarkswith varying degrees of bit error rates. Experimental results and ablationstudies demonstrate the superiority of our proposed method. The code will bereleased at https://github.com/wenyang001/Two-ACIR.

Bitstream-Corrupted JPEG Images are Restorable: Two-stage Compensation and Alignment Framework for Image Restoration