Video De-noising Using Adaptive Temporal and Spatial Filter Based on Mean Square Error Estimation
Author(s) -
Chang-shou Jin,
Jong-Ho Kim,
Yoonsik Choe
Publication year - 2012
Publication title -
journal of broadcast engineering
Language(s) - English
Resource type - Journals
eISSN - 2287-9137
pISSN - 1226-7953
DOI - 10.5909/jbe.2012.17.6.1048
Subject(s) - mean squared error , kernel adaptive filter , adaptive filter , filter (signal processing) , block (permutation group theory) , mathematics , filter design , algorithm , computer science , computer vision , statistics , geometry
In this paper, an adaptive temporal and spatial filter (ATSF) based on mean square error (MSE) estimation is proposed. ATSF is a block based de-noising algorithm. Each noisy block is selectively filtered by a temporal filter or a spatial filter. Multi-hypothesis motion compensated filter (MHMCF) and bilateral filter are chosen as the temporal filter and the spatial filter, respectively. Although there is no original video, we mathematically derivate a formular to estimate the real MSE between a block de-noised by MHMCF and its original block and a linear model is proposed to estimate the real MSE between a block de-noised by bilateral filter and its original block. Finally, each noisy block is processed by the filter with a smaller estimated MSE. Simulation results show that our proposed algorithm achieves substantial improvements in terms of both visual quality and PSNR as compared with the conventional de-noising algorithms.
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