In this paper, we propose an advanced wavelet domain denoising scheme for the Gaussian noise reduction in color video. In the proposed method, we perform the wavelet transform of the luminance component (Y) in full resolution and the wavelet transform of chrominance information (U and V) in a subsampled resolution (2:1) in order to extract edges belonging to luminance and chrominance gradients (in horizontal and vertical directions). We use the low-pass (approximation) subbands of the chrominance channels together with detail (wavelet) bands for recursive motion estimation and adaptive temporal filtering. The final part of the proposed filter is a spatial filter out of the recursive loop. The noise level is monitored and detected automatically, by the gradient histogram approach for each channel separately and the estimated noise variance is used for adapting the algorithm. The results on color video show good video denoising performance for different noise levels. In comparison to the other color video denoising methods, the method performs better both from subjective (visually) and objective point of view. Also, the estimated motion vector field is quite robust against noise and this is useful in other applications such as tracking.

Date Published: 17 September 2005
PDF: 11 pages
Proc. SPIE 5914, Wavelets XI, 59141P (17 September 2005); doi: 10.1117/12.621856

Published in SPIE Proceedings Vol. 5914:
Wavelets XI
Manos Papadakis; Andrew F. Laine; Michael A. Unser, Editor(s)