Adaptive postfiltering of transform coefficients for the reduction of blocking artifacts

This paper proposes a novel postprocessing technique for reducing blocking artifacts in low-bit-rate transform-coded images. The proposed approach works in the transform domain to alleviate the accuracy loss of transform coefficients, which is introduced by the quantization process. The masking effect in the human visual system (HVS) is considered, and an adaptive weighting mechanism is then integrated into the postfiltering. In low-activity areas, since blocking artifacts appear to be perceptually more detectable, a large window is used to efficiently smooth out the artifacts. In order to preserve image details, a small mask, as well as a large central weight, is employed for processing those high-activity blocks, where blocking artifacts are less noticeable due to the masking ability of local background. The quantization constraint is finally applied to the postfiltered coefficients. Experimental results show that the proposed technique provides satisfactory performance as compared to other postfilters in both objective and subjective image quality