Reduction of blocking artifacts in image and video coding

The discrete cosine transform (DCT) is the most popular transform for image and video compression. Many international standards such as JPEG, MPEG, an d H.261 are based on a block-DCT scheme, High compression ratios are obtain ed by discarding information about DCT coefficients that is considered to b e less important. The major drawback is visible discontinuities along block boundaries, commonly referred to as blocking artifacts, These often limit the maximum compression ratios that can be achieved. Various postprocessing techniques have been published that reduce these blocking effects, but mos t of them introduce unnecessary blurring, ringing, or other artifacts. In t his paper, a novel postprocessing algorithm based on Markov random fields ( MRF's) is proposed. It efficiently removes blocking effects while retaining the sharpness of the image and without introducing new artifacts, The degr aded image is first segmented into regions, and then each region is enhance d separately to prevent blurring of dominant edges. A novel texture detecto r allows the segmentation of images containing both texture and monotone ar eas. It finds all texture regions in the image before the remaining monoton e areas are segmented by an MRF segmentation algorithm that has a new edge component incorporated to detect dominant edges more reliably. The proposed enhancement stage then finds the maximum a posteriori estimate of the unkn own original image, which is modeled by an MRF and is therefore Gibbs distr ibuted. A very efficient implementation is presented. Experiments demonstra te that our proposed postprocessor gives excellent results compared to othe r approaches, from both a subjective and an objective viewpoint, Furthermor e, it will be shown that our technique also works for wavelet encoded image s, which typically contain ringing artifacts.