Wavelet video denoising with regularized multiresolution motion estimation
EURASIP Journal on Applied Signal Processing
PCS'09 Proceedings of the 27th conference on Picture Coding Symposium
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 presents three-dimensional (spatio-temporal) Kalman filters for video as the extension of the two-dimensional (2-D) reduced update Kalman filter (RUKF) approach for images. We start out with three-dimensional (3-D) RUKF, a shift-invariant recursive estimator with efficiency advantages over the 3-D Wiener filter. Then, we turn to the motion-compensated extension MC-RUKF, which gives improved performance when coupled with a motion estimator. Since motion compensation sometimes fails, causing severe fluctuations in temporal correlation, we then present multimodel MC-RUKF, to adapt to variation in temporal and spatial correlation, by detecting the local image model out of a class, and using it in MC-RUKF. Finally, we introduce a novel multiscale model detection algorithm for use in high noise environments