Title :
A novel content-adaptive video denoising filter
Author :
Chan, Tai-Wai ; Au, Oscar C. ; Chong, Tak-Song ; Chau, Wing-San
Author_Institution :
Dept. of Electr. & Electron. Eng., Hong Kong Univ. of Sci. & Technol., China
Abstract :
We propose a simple non-linear content-adaptive filter that is efficient in removing noise from a video. The proposed filter is called spatiotemporal varying filter (STVF) and is able to produce optimal results in the sense that it minimizes the weighted least square error. STVF combines the advantages of conventional denoising filters that enable it to decrease the noise variance in smooth areas but at the same time retains the sharpness of edges in object boundaries. Simulation results show that STVF outperforms the conventional denoising methods like low-pass filtering, median filtering and Wiener filtering.
Keywords :
adaptive filters; image denoising; impulse noise; least squares approximations; minimisation; nonlinear filters; random noise; video signal processing; Wiener filtering; content-adaptive filter; content-adaptive video denoising filter; edge sharpness; impulsive noise; low-pass filtering; median filtering; noise variance; nonimpulsive noise; nonlinear filter; spatiotemporal varying filter; weighted least square error minimization; Entropy; Filtering algorithms; Image storage; Kalman filters; Low pass filters; Noise reduction; Signal processing algorithms; Video compression; Videoconference; Wiener filter;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). IEEE International Conference on
Print_ISBN :
0-7803-8874-7
DOI :
10.1109/ICASSP.2005.1415488