Wavelet-Domain Video Denoising Based on Reliability Measures

• Published in: IEEE transactions on circuits and systems for video technology Vol. 16; no. 8; pp. 993 - 1007
• Main Authors: Zlokolica, V., Pizurica, A., Philips, W.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.08.2006; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive filters; Applied sciences; Circuit properties; Cost function; Detection, estimation, filtering, equalization, prediction; Electric, optical and optoelectronic circuits; Electronic circuits; Electronics; Exact sciences and technology; Filtering; Filtration; Frequency filters; Gray-scale; Image processing; Information, signal and communications theory; Motion estimation; Motion measurement; Noise reduction; Orientation; Signal and communications theory; Signal processing; Signal representation. Spectral analysis; Signal, noise; Smoothing methods; Spatial filtering; Telecommunications and information theory; Temporal logic; video denoising; Wavelet; Wavelet coefficients; Wavelet domain; wavelets; Closed loop; Spatial frequency filtering; Motion estimation; Image processing; Refinement method; Noise reduction; Spatial orientation; Adaptive estimation; Adaptive filter; Adaptive method; Temporal logic; video denoising; Wavelets; Gray scale; Wavelet transformation; Wavelet base; Displacement measurement; Signal processing; Cost function; Motion detection; Reliability; Signal analysis; Recursive estimation
• ISSN: 1051-8215; 1558-2205
• DOI: 10.1109/TCSVT.2006.879994

This paper proposes a novel video denoising method based on nondecimated wavelet band filtering. In the proposed method, motion estimation and adaptive recursive temporal filtering are performed in a closed loop, followed by an intra-frame spatially adaptive filter. All processing occurs in the wavelet domain. The paper introduces new wavelet-based motion reliability measures. We make a difference between motion reliability per orientation and reliability per wavelet band. These two reliability measures are employed in different stages of the proposed denoising scheme. The reliability per orientation (horizontal and vertical) measure is used in the proposed motion estimation scheme while the reliability of the estimated motion vectors (MVs) per wavelet band is utilized for subsequent adaptive temporal and spatial filtering. We propose a novel cost function for motion estimation which takes into account the spatial orientation of image structures and their motion matching values. Our motion estimation approach is a novel wavelet-domain three-step scheme, where the refinement of MVs in each step is determined based on the proposed motion reliabilities per orientation. The temporal filtering is performed separately in each wavelet band along the estimated motion trajectory and the parameters of the temporal filter depend on the motion reliabilities per wavelet band. The final spatial filtering step employs an adaptive smoothing of wavelet coefficients that yields a stronger filtering at the positions where the temporal filter was less effective. The results on various grayscale sequences demonstrate that the proposed filter outperforms several state-of-the-art filters visually (as judged by a small test panel) as well as in terms of peak signal-to-noise ratio