A deblocking technique for JPEG decoded image using wavelet transform modulus maxima representation

In this paper, we introduce a local deblocking algorithm for JPEG decoded images using the wavelet transform modulus maxima (WTMM) representation. Under the WTMM representation, we can characterize the blocking effect as: 1) small modulus maxima at block boundaries over smooth regions; 2) noises or irregular structures near strong edges; 3) corrupted edges across block boundaries. The WTMM representation not only provides characterization of the blocking effect, but also enables simple and local operations on those singularities. The proposed algorithm first performs a segmentation to discriminate the texture regions of an image based on the WTMM local regularity variance. We then keep the modulus maxima of these regions, which are of low regularity variation, unchange to avoid the image texture being “over-smoothed” by the algorithm. Then, the singularities on the remaining regions of the blocky image and small modulus maxima at block boundaries are removed. Then, we link up the corrupted edges and regularize the phase of modulus maxima as well as the amplitude of strong edges. Finally, the image is reconstructed using the projection onto convex sets (POCS) technique on the processed WTMM of the JPEG decoded image. This simple algorithm improves the quality of JPEG decoded image in the sense of signal to noise ratio as well as visual quality. We also compare the performance of our algorithm with the previous approaches and show the superiority over them. The most remarkable advantage of the WTMM deblocking algorithm is that it incorporates direct edges and texture operations into the WTMM representation