Motion identification from image sequences: Information theory and pixel selection
Computers & Mathematics with Applications
Efficient video denoising based on dynamic nonlocal means
Image and Vision Computing
Nonrigid motion estimation from a sequence of degraded images
Mathematical and Computer Modelling: An International Journal
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The authors propose a novel adaptive spatiotemporal filter, called the adaptive weighted averaging (AWA) filter, for effective noise suppression in image sequences without introducing visually disturbing blurring artifacts. Filtering is performed by computing the weighted average of image values within a spatiotemporal support along the estimated motion trajectory at each pixel. The weights are determined by optimizing a well defined mathematical criterion, which provides an implicit mechanism for deemphasizing the contribution of the outlier pixels within the spatiotemporal filter support to avoid blurring. The AWA filter is therefore particularly well suited for filtering sequences that contain segments with abruptly changing scene content due to, for example, rapid zooming and changes in the view of the camera. The performance of the proposed AWA filter is compared with that of the spatiotemporal, local linear minimum mean square error (LMMSE) filtering. The results demonstrate that the proposed AWA filter-outperforms the LMMSE filter, especially in the cases of low signal-to-noise ratios and abruptly varying scene content