Paper
3 February 2011 Video denoising using separable 4D nonlocal spatiotemporal transforms
Author Affiliations +
Proceedings Volume 7870, Image Processing: Algorithms and Systems IX; 787003 (2011) https://doi.org/10.1117/12.872569
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States
Abstract
We propose a powerful video denoising algorithm that exploits temporal and spatial redundancy characterizing natural video sequences. The algorithm implements the paradigm of nonlocal grouping and collaborative filtering, where a higher-dimensional transform-domain representation is leveraged to enforce sparsity and thus regularize the data. The proposed algorithm exploits the mutual similarity between 3-D spatiotemporal volumes constructed by tracking blocks along trajectories defined by the motion vectors. Mutually similar volumes are grouped together by stacking them along an additional fourth dimension, thus producing a 4-D structure, termed group, where different types of data correlation exist along the different dimensions: local correlation along the two dimensions of the blocks, temporal correlation along the motion trajectories, and nonlocal spatial correlation (i.e. self-similarity) along the fourth dimension. Collaborative filtering is realized by transforming each group through a decorrelating 4-D separable transform and then by shrinkage and inverse transformation. In this way, collaborative filtering provides estimates for each volume stacked in the group, which are then returned and adaptively aggregated to their original position in the video. Experimental results demonstrate the effectiveness of the proposed procedure which outperforms the state of the art.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Matteo Maggioni, Giacomo Boracchi, Alessandro Foi, and Karen Egiazarian "Video denoising using separable 4D nonlocal spatiotemporal transforms", Proc. SPIE 7870, Image Processing: Algorithms and Systems IX, 787003 (3 February 2011); https://doi.org/10.1117/12.872569
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CITATIONS
Cited by 51 scholarly publications and 3 patents.
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KEYWORDS
Video

Transform theory

Denoising

Electronic filtering

Video acceleration

Filtering (signal processing)

Detection and tracking algorithms

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