Impulse Noise Detection and Filtering Based On Adaptive Weighted Median Filter (original) (raw)
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An Improved Adaptive Median Filtering Method for Impulse Noise Detection
International Journal of Recent …, 2009
An Impulse noise detection & removal with adaptive filtering approach is proposed to restore images corrupted by salt & pepper noise. The proposed algorithm works well for suppressing impulse noise with noise density from 5 to 60% while preserving image details. The difference of current central pixel with median of local neighborhood pixels is used to classify the central pixel as noisy or noise-free. The noise is attenuated by estimating the values of the noisy pixels with a switching based median filter applied exclusively to those neighborhood pixels not labeled as noisy. The size of filtering window is adaptive in nature, and it depends on the number of noise-free pixels in current filtering window. Simulation results indicate that this filter is better able to preserve 2-D edge structures of the image and delivers better performance with less computational complexity as compared to other denoising algorithms existing in literature.
Design and Development of an Improved Adaptive Median Filtering Method for Impulse Noise Detection
International Journal of Computer and Electrical Engineering, 2009
An Impulse noise detection & removal with adaptive filtering approach is proposed to restore images corrupted by salt & pepper noise. The proposed algorithm works well for suppressing impulse noise with noise density from 5 to 60% while preserving image details. The difference of current central pixel with median of local neighborhood pixels is used to classify the central pixel as noisy or noise-free. The noise is attenuated by estimating the values of the noisy pixels with a switching based median filter applied exclusively to those neighborhood pixels not labeled as noisy. The size of filtering window is adaptive in nature, and it depends on the number of noise-free pixels in current filtering window. Simulation results indicate that this filter is better able to preserve 2-D edge structures of the image and delivers better performance with less computational complexity as compared to other denoising algorithms existing in literature.
Impulse Noise Detection and Removal Method Based on Modified Weighted Median
International Journal of Software Innovation
Impulse noise generally occurs because of bit errors in progression of image acquisition and transmission. It is well known that median filtering method is an impulse noise removal method. Lots of modified median filters have been proposed in the last decades to improve the methods for noise suppression and detail preservation, which have their own deficiencies while identifying and restoring noise pixels. In this article, after deeply analyzing the reasons, such as decreased noise detection and noise removal accuracy that forms the basis of the deficiencies, this article proposes a modified weighted median filter method for color images corrupted by salt-and-pepper noise. In this method, a pixel is classified into either “noise free pixel” or “noise pixel” by checking the center pixel in the current filtering window with the extreme values (0 or 255) for an 8-bit image using noise detection step. Directional differences and the number of “good” pixels in the current filtering windo...
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 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 .
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.
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.