Wavelet video denoising with regularized multiresolution motion estimation
EURASIP Journal on Applied Signal Processing
EURASIP Journal on Advances in Signal Processing
Video denoising using spatio-temporal filtering
Proceedings of the 2nd international conference on Scalable information systems
Video Restoration with Motion Prediction Based on the Multiresolution Wavelet Analysis
Neural Information Processing
Image sequence denoising via sparse and redundant representations
IEEE Transactions on Image Processing
Pixel domain spatio-temporal denoising for archive videos
ISCIS'06 Proceedings of the 21st international conference on Computer and Information Sciences
Efficient video denoising based on dynamic nonlocal means
Image and Vision Computing
PCA based video denoising in a non-local means framework
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing
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We develop a new filter which combines spatially adaptive noise filtering in the wavelet domain and temporal filtering in the signal domain. For spatial filtering, we propose a new wavelet shrinkage method, which estimates how probable it is that a wavelet coefficient represents a "signal of interest" given its value, given the locally averaged coefficient magnitude and given the global subband statistics. The temporal filter combines a motion detector and recursive time-averaging. The results show that this combination outperforms single resolution spatio-temporal filters in terms of quantitative performance measures as well as in terms of visual quality. Even though our current implementation of the new filter does not allow real-time processing, we believe that its optimized software implementation could be used for real- or near real-time filtering.