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Research Article | Open Access

Salt and pepper noise removal in surveillance video based on low-rank matrix recovery

Yongxia Zhang1, Yi Liu1, Xuemei Li1( ), Caiming Zhang1,2
School of Computer Science and Technology, Shandong University, Jinan 250101, China.
Shandong University of Finance and Economics, Shandong Provincial Key Laboratory of Digital Media Technology, Jinan 250014, China.
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Abstract

This paper proposes a new algorithm based on low-rank matrix recovery to remove salt & pepper noise from surveillance video. Unlike single image denoising techniques, noise removal from video sequences aims to utilize both temporal and spatial information. By grouping neighboring frames based on similarities of the whole images in the temporal domain, we formulate the problem of removing salt & pepper noise from a video tracking sequence as a low-rank matrix recovery problem. The resulting nuclear norm and L1-norm related minimization problems can be efficiently solved by many recently developed methods. To determine the low-rank matrix, we use an averaging method based on other similar images. Our method can not only remove noise but also preserve edges and details. The performance of our proposed approach compares favorably to that of existing algorithms and gives better PSNR and SSIM results.

Keywords

multimedia computingnoise cancellationsignal denoisingsparse matricesvideo signal processingvideo surveillance

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Computational Visual Media
Volume 1 Issue 1,
March 2015
Pages 59-68
DOI: 10.1007/s41095-015-0005-5
Cite this article:
Zhang Y, Liu Y, Li X, et al. Salt and pepper noise removal in surveillance video based on low-rank matrix recovery. Computational Visual Media, 2015, 1(1): 59-68. https://doi.org/10.1007/s41095-015-0005-5

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Revised: 10 October 2014
Accepted: 26 January 2015
Published: 08 August 2015
© The Author(s) 2015

This article is published with open access at Springerlink.com

This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
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