Removal of High Density Salt and Pepper Noise through Hybrid of Negative Selection Algorithm and Median Filter
18 Dec 2014-International Journal of Computer Applications (Foundation of Computer Science (FCS))-Vol. 107, Iss: 15, pp 20-24
TL;DR: A new improved NSA based switching median filter which has the capability to decrease the high density of the noise from images and also outperforms over others when input image is noise free and ability to preserves the edges by using the gradient based smoothing.
Abstract: Noise in images has become one of the significant concerns in digital image processing. Many digital image based techniques produce inaccurate results when noise is presented in the digital images. So many researchers have proposed new and modified techniques so far to reduce or remove noise from images. Different kind of enhancement in the filters has been proposed so far. But most of filters put artefacts while doing their work. Many filters fail when noise density in the images is very high. Some filters results poor for edges. This paper has proposed a new improved NSA based switching median filter which has the capability to decrease the high density of the noise from images and also outperforms over others when input image is noise free. The proposed method has also ability to preserves the edges by using the gradient based smoothing. The proposed technique has been designed and implemented in MATLAB tool using image processing toolbox. Different kind of the digital images has been taken for experimental purpose. Comparative analysis has shown that the proposed algorithm is quite effective over the available techniques.
Citations
More filters
06 Dec 2016
TL;DR: In this paper, a lowpass filter is implemented through wavelet thresholding, attenuating error level noises and confirming the method’s efficiency at noise filtering while preserving necessary error levels.
Abstract: 8 In this paper a method for detection of image forgery in lossy compressed digital images known as error level analysis (ELA) is presented and it’s noisy components are filtered with automatic wavelet soft-thresholding. With ELA, a lossy compressed image is recompressed at a known error rate and the absolute differences between these images, known as error levels, are computed. This method might be weakened if the image noise generated by the compression scheme is too intense, creating the necessity of noise filtering. Wavelet thresholding is a proven denoising technique which is capable of removing an image’s noise avoiding altering other components, like high frequencies regions, by thresholding the wavelet transform coefficients, thus not causing blurring. Despite its effectiveness, the choice of the threshold is a known issue. However there are some approaches to select it automatically. In this paper, a lowpass filter is implemented through wavelet thresholding, attenuating error level noises. An efficient method to automatically determine the threshold level is used, showing good results in threshold selection for the presented problem. Standard test images have been doctored to simulate image tampering, error levels for these images are computed and wavelet thresholding is performed to attenuate noise. Results are presented, confirming the method’s efficiency at noise filtering while preserving necessary error levels. 9
2 citations
Cites background or methods from "Removal of High Density Salt and Pe..."
...Passive blind image forensics are well documented, featuring surveys such as Farid (2009b); Ng 47 et al. (2006). Current methods dwell on detecting cloning, which is essentially cutting and pasting in 48 an image Fridrich et al. (2003); Popescu and Farid (2004a); resampling, originated from processes of 49 resizing, rotating or stretching portions of pixels Popescu and Farid (2004b); Kirchner (2008); Mahdian 50 and Saic (2007); Prasad and Ramakrishnan (2006); splicing or matting, the process of combining two or 51 more images into a single composite, usually taking care to match borders Farid (1999); Ng and Chang 52 (2004) and statistical analysis, where statistical properties of natural images are exploited to detect image 53 manipulation Farid and Lyu (2003); Bayram et al....
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...Passive blind image forensics are well documented, featuring surveys such as Farid (2009b); Ng 47 et al. (2006). Current methods dwell on detecting cloning, which is essentially cutting and pasting in 48 an image Fridrich et al....
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...Passive blind image forensics are well documented, featuring surveys such as Farid (2009b); Ng 47 et al....
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01 Jan 2022
1 citations
References
More filters
TL;DR: Based on two types of image models corrupted by impulse noise, two new algorithms for adaptive median filters are proposed that have variable window size for removal of impulses while preserving sharpness and are superior to standard median filters.
Abstract: Based on two types of image models corrupted by impulse noise, we propose two new algorithms for adaptive median filters. They have variable window size for removal of impulses while preserving sharpness. The first one, called the ranked-order based adaptive median filter (RAMF), is based on a test for the presence of impulses in the center pixel itself followed by a test for the presence of residual impulses in the median filter output. The second one, called the impulse size based adaptive median filter (SAMF), is based on the detection of the size of the impulse noise. It is shown that the RAMF is superior to the nonlinear mean L/sub p/ filter in removing positive and negative impulses while simultaneously preserving sharpness; the SAMF is superior to Lin's (1988) adaptive scheme because it is simpler with better performance in removing the high density impulsive noise as well as nonimpulsive noise and in preserving the fine details. Simulations on standard images confirm that these algorithms are superior to standard median filters. >
1,172 citations
Book•
01 Jan 1997
TL;DR: In this article, statistical analysis and optimization of nonlinear filter methods based on order statistics Stack Filters Multistage and Hybrid Filters Discussion Exercises Bibliography Index Index.
Abstract: Nonlinear Signal Processing Signal Processing Model Signal and Noise Models Fundamental Problems in Noise Removal Algorithms Statistical Preliminaries Random Variables and Distributions Signal and Noise Models Estimation Some Useful Distributions 1001 Solutions Trimmed Mean Filters Other Trimmed Mean Filters L-Filters C-Filters (Ll-Filters) Weighted Median Filters Ranked-Order and Weighted Order Statistic Filters Multistage Median Filters Median Hybrid Filters Edge-Enhancing Selective Filters Rank Selection Filters M-Filters R-Filters Weighted Majority with Minimum Range Filters Nonlinear Mean Filters Stack Filters Generalizations of Stack Filters Morphological Filters Soft Morphological Filters Polynomial Filters Data-Dependent Filters Decision-Based Filters Iterative, Cascaded, and Recursive Filters Some Numerical Measures of Nonlinear Filters Discussion Statistical Analysis and Optimization of Nonlinear Filters Methods Based on Order Statistics Stack Filters Multistage and Hybrid Filters Discussion Exercises Bibliography Index
729 citations
TL;DR: A new impulse noise detection technique for switching median filters is presented, which is based on the minimum absolute value of four convolutions obtained using one-dimensional Laplacian operators, and is directed toward improved line preservation.
Abstract: A new impulse noise detection technique for switching median filters is presented, which is based on the minimum absolute value of four convolutions obtained using one-dimensional Laplacian operators. Extensive simulations show that the proposed filter provides better performance than many of the existing switching median filters with comparable computational complexity. In particular, the proposed filter is directed toward improved line preservation.
688 citations
"Removal of High Density Salt and Pe..." refers methods in this paper
...So a modified median filter is used [3], [4]....
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TL;DR: A new decision-based algorithm is proposed for restoration of images that are highly corrupted by impulse noise that removes the noise effectively even at noise level as high as 90% and preserves the edges without any loss up to 80% of noise level.
Abstract: A new decision-based algorithm is proposed for restoration of images that are highly corrupted by impulse noise. The new algorithm shows significantly better image quality than a standard median filter (SMF), adaptive median filters (AMF), a threshold decomposition filter (TDF), cascade, and recursive nonlinear filters. The proposed method, unlike other nonlinear filters, removes only corrupted pixel by the median value or by its neighboring pixel value. As a result of this, the proposed method removes the noise effectively even at noise level as high as 90% and preserves the edges without any loss up to 80% of noise level. The proposed algorithm (PA) is tested on different images and is found to produce better results in terms of the qualitative and quantitative measures of the image
679 citations
"Removal of High Density Salt and Pe..." refers methods in this paper
...To overcome the above drawback, Decision Based Algorithm (DBA) is proposed [5]....
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TL;DR: Results clearly show that the proposed switching median filter substantially outperforms all existing median-based filters, in terms of suppressing impulse noise while preserving image details, and yet, the proposed BDND is algorithmically simple, suitable for real-time implementation and application.
Abstract: A novel switching median filter incorporating with a powerful impulse noise detection method, called the boundary discriminative noise detection (BDND), is proposed in this paper for effectively denoising extremely corrupted images. To determine whether the current pixel is corrupted, the proposed BDND algorithm first classifies the pixels of a localized window, centering on the current pixel, into three groups-lower intensity impulse noise, uncorrupted pixels, and higher intensity impulse noise. The center pixel will then be considered as "uncorrupted," provided that it belongs to the "uncorrupted" pixel group, or "corrupted." For that, two boundaries that discriminate these three groups require to be accurately determined for yielding a very high noise detection accuracy-in our case, achieving zero miss-detection rate while maintaining a fairly low false-alarm rate, even up to 70% noise corruption. Four noise models are considered for performance evaluation. Extensive simulation results conducted on both monochrome and color images under a wide range (from 10% to 90%) of noise corruption clearly show that our proposed switching median filter substantially outperforms all existing median-based filters, in terms of suppressing impulse noise while preserving image details, and yet, the proposed BDND is algorithmically simple, suitable for real-time implementation and application.
614 citations