z-logo
open-access-imgOpen Access
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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom