Characterization of Signals from Multiscale Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
De-noising by soft-thresholding
IEEE Transactions on Information Theory
A deblocking technique for block-transform compressed image using wavelet transform modulus maxima
IEEE Transactions on Image Processing
Projection-based spatially adaptive reconstruction of block-transform compressed images
IEEE Transactions on Image Processing
A deblocking algorithm for JPEG compressed images using overcomplete wavelet representations
IEEE Transactions on Circuits and Systems for Video Technology
Reduction of blocking artifact in block-coded images using wavelet transform
IEEE Transactions on Circuits and Systems for Video Technology
A deblocking filter with two separate modes in block-based video coding
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
MLP for adaptive postprocessing block-coded images
IEEE Transactions on Circuits and Systems for Video Technology
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In this paper, we propose a hybrid deblocking algorithm to improve the visual quality of block-based low bit rate coded images, those are processed both spatial and wavelet domains. The proposed algorithm reduces the blocking artifacts using the statistical characteristics of block discontinuity as well as the lipschitz regularity along the behavior of wavelet coefficients across scales. In this algorithm, detection of blocking artifacts and block boundary classification is performed in spatial domain to reduce the computational complexity for performing the wavelet transform and inverse wavelet transform for all image, and adaptive filtering is processed in spatial or wavelet domains. Spatial adaptive filtering is processed to reduce the blocking artifacts in smooth region with the blocking artifacts. For complex or mixed region, the Lipschitz regularity is obtained to analyze the evolution of the local maxima of the wavelet transform modulus across scales and these irregular singularities are adaptively removed in wavelet domain. Experimental results show that the proposed algorithm produced better results than those of conventional algorithms both PSNR and visual quality.