Improved decoding of compressed images received over noisy channels
This paper presents an image communication system with improved decoding of compressed image information. A convolutional code protects the compressed image information from channel noise while a Reed-Solomon outer code gives additional protection to the critical image header information. A post-processor detects uncorrected channel errors in the reconstructed image and feeds error location information to a list-based iterative trellis decoder. This list-based decoder provides significant improvement in image quality. Experimental results are given for varying channel SNR and for varying bit rate.