A joint source-channel distortion model for JPEG compressed images

The need for efficient joint source-channel coding is growing as new multimedia services are introduced in commercial wireless communication systems. An important component of practical joint source-channel coding schemes is a distortion model to measure the quality of compressed digital multimedia such as images and videos. Unfortunately, models for estimating the distortion due to quantization and channel bit errors in a combined fashion do not appear to be available for practical image or video coding standards. This paper presents a statistical model for estimating the distortion introduced in progressive JPEG compressed images due to both quantization and channel bit errors. Important compression techniques such as Huffman coding, DPCM coding, and run-length coding are included in the model. Examples show that the distortion in terms of peak signal to noise ratio can be predicted within a 2 dB maximum error.