Transform-domain postprocessing of DCT-coded images

Data compression algorithms are developed to transmit massive image data under limited channel capacity. When a channel rate is not sufficient to transmit good quality compressed images, a degraded image after compression is reconstructed at the decoder. In this situation, a postprocessor can be used to improve the receiver image quality. Ideally, the objective of postprocessing is to restore the original pictures from the received distorted pictures. However, when the received pictures are heavily distorted, there may not exist enough information to restore the original images. Then, what a postprocessor can do is to reduce the subjective artifact rather than to minimize the differences between the received and the original images. In this paper, we propose two postprocessing techniques, namely, error pattern compensation and inter-block transform coefficient adjustment. Since Discrete Cosine Transform (DCT) coding is widely adopted by the international image transmission standards, our postprocessing schemes are proposed in the DCT domain. When the above schemes are applied to highly distorted images, quite noticeable subjective improvement can be observed.