Salt and pepper noise removal in video using adaptive decision based median filter

Veerakumar, T.; Esakkirajan, S.; Vennila, Ila

doi:10.1109/mspct.2011.6150444

Cited by 12 publications

(13 citation statements)

References 6 publications

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“…Firstly, to show the importance of information in the temporal domain, we compare our method with other recent single frame denoising algorithms: MDBUTMF [11], DMPMF [8], and ADBMF [7]; they focus on removing salt & pepper noise from video frame by frame. The visual quality can be evaluated in Figs.…”

Section: Methodsmentioning

confidence: 99%

“…Generally, these algorithms do not work well when the video sequences are corrupted by some other types of noise such as salt & pepper noise. Of course, there have been many research works on removing salt & pepper noise from a single image [7][8][9][10][11]. One of the common and simplest methods of removing salt & pepper noise is the median filter (MF) along with its variants.…”

Section: Related Workmentioning

confidence: 99%

“…In Ref. [7], the adaptive decision based median filter (ADBMF) is used to remove salt & pepper noise from video by applying this filter to each frame as single image without considering information in the temporal domain. The adaptive temporal averaging (ATA) algorithm [2] takes advantage of the similarity of frames in the temporal domain to remove Gaussian noise from image sequences by averaging similar neighboring frames.…”

Section: Related Workmentioning

confidence: 99%

“…But surveillance video sequences usually have very high temporal redundancy which means neighboring frames have high similarity in structure which should be effectively used for better performance [2,7,15]. Patch-based schemes can also be applied to video sequences, but unlike in single image denoising, the block matching process is not only applied within each image to which the referenced patch belongs, but also within neighboring frames.…”

Section: Related Workmentioning

confidence: 99%

“…Salt & pepper noise corrupts the signal by replacing the original pixel value with either the maximum or minimum gray level value; it severely impacts the accuracy and efficiency of information retrieval from such signals. Many existing algorithms for removing salt & pepper noise from sequences use a single-image denoising method on each frame of video [7]. Such methods do not take advantage of the information in the temporal domain.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

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

Zhang

Liu

et al. 2015

Comp. Visual Media

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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 lowrank 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.

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Section: Methodsmentioning

confidence: 99%