International Journal of Computer Vision - Special issue on statistical and computational theories of vision: modeling, learning, sampling and computing, Part I
A Non-Local Algorithm for Image Denoising
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Adaptive fuzzy filtering for artifact reduction in compressed images and videos
IEEE Transactions on Image Processing
IEEE Transactions on Multimedia
Adaptive blocking artifact reduction using wavelet-based block analysis
IEEE Transactions on Consumer Electronics
Edge statistics-based image scale ratio and noise strength estimation in DCT-coded images
IEEE Transactions on Consumer Electronics
Processing JPEG-compressed images and documents
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Deblocking of block-transform compressed images using weighted sums of symmetrically aligned pixels
IEEE Transactions on Image Processing
Postprocessing of Low Bit-Rate Block DCT Coded Images Based on a Fields of Experts Prior
IEEE Transactions on Image Processing
Multiresolution Bilateral Filtering for Image Denoising
IEEE Transactions on Image Processing
Quality Assessment of Deblocked Images
IEEE Transactions on Image Processing
Classified perceptual coding with adaptive quantization
IEEE Transactions on Circuits and Systems for Video Technology
Reduction of blocking artifacts in image and video coding
IEEE Transactions on Circuits and Systems for Video Technology
Noise estimation for blocking artifacts reduction in DCT coded images
IEEE Transactions on Circuits and Systems for Video Technology
An efficient wavelet-based deblocking algorithm for highly compressed images
IEEE Transactions on Circuits and Systems for Video Technology
Blocking artifacts suppression in block-coded images using overcomplete wavelet representation
IEEE Transactions on Circuits and Systems for Video Technology
An optimization approach for removing blocking effects in transform coding
IEEE Transactions on Circuits and Systems for Video Technology
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Blocking artifacts often exist in the images compressed by standards, such as JPEG and MPEG, which causes serious image degradation. Many algorithms have been proposed in the last decade to alleviate this degradation by reducing the quantization noise. Unfortunately, these algorithms only produce satisfying results under an unreasonable assumption that noise magnitude has been given. However, in most applications, the user only gets inferior image copy, without any side information about noise distribution, therefore the efficiency of existing denoise algorithms is significantly reduced. In this paper, a new metric is first given to evaluate the blocking artifacts; and then non-local means filter is applied to remove quantization noise on the blocks. During the process, nonlocal means filters with different variances are used to do deblocking, and their efficiencies are recorded as the references. The deblocked image is finally the one combined with all blocks filtered with the optimal parameters. We prove with experimental results that the proposed algorithm constantly outperforms the peer ones on all kinds of images.