IJERT-Nonparametric switching median filter for the removal of low level impulse noise (original) (raw)
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Progressive switching median filter for the removal of impulse noise from highly corrupted images
IEEE Transactions on Circuits and Systems Ii: Analog and Digital Signal Processing, 1999
A new median-based filter, progressive switching median (PSM) filter, is proposed to restore images corrupted by salt-pepper impulse noise. The algorithm is developed by the following two main points: 1) switching scheme-an impulse detection algorithm is used before filtering, thus only a proportion of all the pixels will be filtered and 2) progressive methods-both the impulse detection and the noise filtering procedures are progressively applied through several iterations. Simulation results demonstrate that the proposed algorithm is better than traditional median-based filters and is particularly effective for the cases where the images are very highly corrupted.
A Modified Non Linear Median Filter for the Removal of Medium Density Random Valued Impulse Noise
International Journal of Computer Applications, 2016
In the field of image processing, elimination of noise from digital images plays a vital role. Effective detection of noisy pixel based on median value and an efficient algorithm for the estimation and replacement of noisy pixel has been carried out in this proposed method in which replacement of noisy pixel is carried out twice, which results in better preservation of image details. The presence of high performing detection stage for the detection noisy pixel makes the proposed method suitable in the case of high density random valued impulse noise, hence the proposed method yields better image quality with improved peak signal to noise ratio (PSNR) and reduced mean square error (MSE). Results of proposed method has been compared with many other standard median based switching filters in terms of visual and quantitative measures and the performance of the proposed method is presented.
A Modified Switching Median Filter for Reduction of Impulse Noise
This paper presents a new modified switching median filtering technique using fuzzy logic in image processing. This filter is able to remove impulse noise in digital images while preserving image details very well. The performances are compared with other filters such as median, center weighted median and traditional switching median filters for different levels of noise densities in terms of peak signal to noise ratio (PSNR). The subjective evaluations of the filters are also analyzed through various figures.
Universal Impulse Noise Suppression Using Extended Efficient Nonparametric Switching Median Filter
MATEC Web of Conferences
This paper presents a filtering algorithm called extended efficient nonparametric switching median (EENPSM) filter. The proposed filter is composed of a nonparametric easy to implement impulse noise detector and a recursive pixel restoration technique. Initially, the impulse detector classifies any possible impulsive noise pixels. Subsequently, the filtering phase replaces the detected noise pixels. In addition, the filtering phase employs fuzzy reasoning to deal with uncertainties present in local information. Contrary to the existing conventional filters that only focus on a particular impulse noise model, the EENPSM filter is capable of filtering all kinds of impulse noise (i.e. the random-valued and/or fixed-valued impulse noise models). Extensive qualitative and quantitative evaluations have shown that the EENPSM method performs better than some of the existing methods by giving better filtering performance.
IJERT-Adaptive Window Size Median Based Filter for Impulse Noise Removal in Digital Images
International Journal of Engineering Research and Technology (IJERT), 2014
https://www.ijert.org/adaptive-window-size-median-based-filter-for-impulse-noise-removal-in-digital-images https://www.ijert.org/research/adaptive-window-size-median-based-filter-for-impulse-noise-removal-in-digital-images-IJERTV3IS080755.pdf In this paper, a new non-linear filter called 'adaptive window size median based filter' for removing salt and pepper noise and random valued impulse noise with edge and detail preservation is presented. In the proposed method, the corrupted pixels are replaced by the median value of the uncorrupted pixels in the filtering window after identifying the impulse pixel based on threshold values. Since the proposed algorithm takes a decision whether the pixel under test is corrupted or not, it works well up to a noise density as high as 70% with much lower computation time compared to the other standard techniques. Experimental results clearly indicate that the proposed method surpasses many of the existing methods such as standard median filter, weighted median filter, centre weighted median filter, recursive weighted median filter, progressive switching median filter and other proposed decision based algorithm in terms of visual quality and quantitative measures.
Adaptive Window Size Median Based Filter for Impulse Noise Removal in Digital Images
International journal of engineering research and technology, 2014
In this paper, a new non-linear filter called ‘adaptive window size median based filter’ for removing salt and pepper noise and random valued impulse noise with edge and detail preservation is presented. In the proposed method, the corrupted pixels are replaced by the median value of the uncorrupted pixels in the filtering window after identifying the impulse pixel based on threshold values. Since the proposed algorithm takes a decision whether the pixel under test is corrupted or not, it works well up to a noise density as high as 70% with much lower computation time compared to the other standard techniques. Experimental results clearly indicate that the proposed method surpasses many of the existing methods such as standard median filter, weighted median filter, centre weighted median filter, recursive weighted median filter, progressive switching median filter and other proposed decision based algorithm in terms of visual quality and quantitative measures.
Scientific Research and Essays, 2011
Switching Median Filter with Boundary Discriminative Noise Detection (BDND) is one of the useful methods that are capable to restore digital images which have been extremely corrupted by universal impulse noise. Following the fundamental framework of the switching median filter, the construction of BDND can be divided into two stages. The first stage classifies the pixels into either "noise" or "noisefree" pixels, while the second stage restores the image by changing only the intensity values of the "noise" pixels. Unfortunately, the originally proposed BDND employs sorting operations in both of its stages. This condition makes the originally proposed BDND computationally expensive. Therefore, in this paper, an implementation of BDND with reduced computational time is suggested. This reduction is achieved mainly by manipulating the local histograms' properties. Experimental results show that the proposed implementation successfully produces the same results as the originally proposed BDND, but with much shorter processing time.
A new adaptive median filtering technique for removal of impulse noise from images
Proceedings of the 2011 International Conference on Communication, Computing & Security - ICCCS '11, 2011
This paper proposes an fuzzy based adaptive mean filtering (FBAMF) scheme to remove high density impulse noise from images. The FBAMF is a two-stage filter where, in the first stage, a fuzzy detection technique is used to differentiate between corrupted and uncorrupted pixel by calculating the membership value of each and every pixel. Then, the corrupted pixel subjected to the second stage where they are replaced by mean value of uncorrupted neighbouring pixels selected from a window adaptively. If the numbers of uncorrupted pixels in the selected window are not sufficient, a window of next higher size is chosen. Thus, window size is automatically adapted based on the density of noise in the image. As a result window size may vary pixel to pixel while filtering. Comparison shows the proposed filter effectively removes the impulse noise with significant image quality compared with conventional method such as the Standard Median Filter(SMF), Adaptive Median Filter(AMF), Progressive Switching Median Filter(PSMF) and recently proposed methods such as Efficient Decision Based Algorithm (EDBA), Improved Efficient Decision-Based Algorithm (IDBA) and fuzzy-based decision algorithm (FBDA). The visual and quantitative results show that the performance of the proposed filter in the preservation of edges and details is better even at noise level as high as 95%. The efficiency of the proposed algorithm is evaluated using different standard images.
Simple adaptive median filter for the removal of impulse noise from highly corrupted images
IEEE Transactions on Consumer Electronics, 2000
This paper presents a simple, yet efficient way to remove impulse noise from digital images. This novel method comprises two stages. The first stage is to detect the impulse noise in the image. In this stage, based on only the intensity values, the pixels are roughly divided into two classes, which are "noise-free pixel" and "noise pixel". Then, the second stage is to eliminate the impulse noise from the image. In this stage, only the "noise-pixels" are processed. The "noise-free pixels" are copied directly to the output image. The method adaptively changes the size of the median filter based on the number of the "noise-free pixels" in the neighborhood. For the filtering, only "noise-free pixels" are considered for the finding of the median value. The results from 100 test images showed that this proposed method surpasses some of the state-of-art methods, and can remove the noise from highly corrupted images, up to noise percentage of 95%. Average processing time needed to completely process images of 1600×1200 pixels with 95% noise percentage is less than 2.7 seconds. Because of its simplicity, this proposed method is suitable to be implemented in consumer electronics products such as digital television, or digital camera 1 .