EURASIP Journal on Advances in Signal Processing
Real-Time Wavelet-Spatial-Activity-Based Adaptive Video Enhancement Algorithm for FPGA
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Patch-based video processing: a variational Bayesian approach
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
Image sequence denoising via sparse and redundant representations
IEEE Transactions on Image Processing
Video activity analysis based on 3D wavelet statistical properties
ICACT'09 Proceedings of the 11th international conference on Advanced Communication Technology - Volume 3
A new fuzzy motion and detail adaptive video filter
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
Fast Multi-Hypothesis Motion Compensated Filter for Video Denoising
Journal of Signal Processing Systems
Video frames reconstruction based on time-frequency analysis and Hermite projection method
EURASIP Journal on Advances in Signal Processing - Special issue on time-frequency analysis and its applications to multimedia signals
Enhancing video denoising algorithms by fusion from multiple views
ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part I
Efficient video denoising based on dynamic nonlocal means
Image and Vision Computing
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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