Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
An Algorithm for Total Variation Minimization and Applications
Journal of Mathematical Imaging and Vision
Adapted Total Variation for Artifact Free Decompression of JPEG Images
Journal of Mathematical Imaging and Vision
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
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This paper proposes an enhanced reconstruction method of AVC/H.264 intra video based on Motion Compensated Temporal Filtering (MCTF) and Total-Variation (TV) regularization. The MCTF attenuates temporal fluctuations in block transform coefficient values of individual decoded video frames on the basis of Motion Estimation (ME). However, the attenuated block transform coefficients lead to spatial discontinuities on the associated image area. The TV regularization technique reduces the spatial discontinuities, and also suppresses quantization noises of the image edge vicinities that are supposed to belong to a smooth object while keeping the image edge sharpness. The proposed reconstruction method thus enhances the quality of decoded video frames degraded by flicker artifacts and ringing noises. Simulation results show that the proposed method improves the subjective video quality of AVC/H.264 intra video, and the attainable bit rate up to 16.1% at the same objective video quality.