Effective removal of Noise from Videos using Low Rank Matrix Completion

  K.Praveen Kumar,  N.Lalitha,  P.Suresh

Most existing video denoising algorithms assume a single statistical model of image noise, e.g. Salt and Pepper noise, Gaussian noise, but in real time we will have to remove different types of noises from the video. In this paper, we present a new video denoising algorithm capable of removing serious mixed noise from the video data. We formulate the problem of removing mixed noise as a low-rank matrix completion problem, by grouping similar patches in both spatial and temporal domain, which leads to a denoising scheme without strong assumptions on the statistical properties of noise. The robustness and effectiveness of our proposed denoising algorithm on removing mixed noise, e.g. heavy Gaussian noise mixed with impulsive noise, is validated in the experiments and our proposed approach compares favorably against a few denoising algorithms.

Keywords-

Unique Identification Number - IJEDR1704124
Page Number(s) - 752-758
Pubished in - Volume 5 | Issue 4 | November 2017
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  K.Praveen Kumar,  N.Lalitha,  P.Suresh,   "Effective removal of Noise from Videos using Low Rank Matrix Completion", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.5, Issue 4, pp.752-758, November 2017, Available at :http://www.ijedr.org/papers/IJEDR1704124.pdf