High-frequency error recovery in JPEG XR coded images

Image data compressed with JPEG XR when transmitted over error-prone channels is severely distorted. In fact, due to the adaptive coding strategies used by the codec, even a single bit error causes a mismatch in the alignment of the reading position from the bitstream, leading to completely different images at the decoder side. We propose an extension to the JPEG XR algorithm, consisting in an error recovery process enabling the decoder to realign itself to the right bitstream position and to correctly decode the most part of the image. We have performed several experiments using different encoder parameter and different error probabilities while image distortion is measured by PSNR objective metric. The simplicity of the proposed algorithm adds very little computational overhead and seems very promising as confirmed by objective image quality results in experimental tests.