Application of singularity detection for the deblocking of JPEG decoded images

The blocking effect is considered as the most disturbing artifact of JPEG decoded images. Many researchers have suggested various methods to tackle this problem. Recently, the wavelet transform modulus maxima (WTMM) approach was proposed and gives a significant improvement over the previous methods in terms of signal-to-noise ratio (SNR) and visual quality. However, the WTMM deblocking algorithm is an iterative algorithm that requires a long computation time to reconstruct the processed WTMM to obtain the deblocked image. In this work, a new wavelet-based algorithm for JPEG image deblocking is proposed. The new algorithm is based on the idea that besides using the WTMM, the singularity of an image can also be detected by computing the sums of the wavelet coefficients inside the so-called “directional cone of influence” in different scales of the image. The new algorithm has the advantage over the WTMM approach in that it can effectively identify the edge and smooth regions of an image irrespective of the discontinuities introduced by the blocking effect. It is an improvement over the WTMM approach in that only a simple inverse wavelet transform is required to reconstruct the processed wavelet coefficients to obtain the deblocked image. As with the WTMM approach, the new algorithm gives consistent and significant improvement over the previous methods for JPEG image deblocking