A fuzzy impulse noise detection and reduction method

Schulte, Stefan; Nachtegael, Mike; Witte, Valérie De; Weken, Dietrich Van der; Kerre, Etienne

doi:10.1109/tip.2005.864179

Cited by 222 publications

(124 citation statements)

References 17 publications

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“…It can be extended into other fields such as archeology, Medical Image processing, Remote sensing etc. The existing system is available for reducing fat-tailed noise like impulse noise [35,36]. Median filter [37,38,39] and Low-pass filters are in job at present.…”

Section: Resultsmentioning

confidence: 99%

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A Comparative Study of Gaussian Noise Removal Methodologies for Gray Scale Images

Tulin¹

2017

IJCA

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Image filtering is a technique to preserve important signal elements such as edges, smoothing the details of the image to make images appear clear and sharpener. Among all the non linear concepts to suppress Gaussian noise the fuzzy logic based approaches are important as they are capable of reasoning with vague and uncertain information. In this study, have made comparative study with the existing noise reduction methods where the images contaminated with Gaussian noise and found the best result by using fuzzy image filter with the help of fuzzy rules which make use of membership functions. In this article, to perform fuzzy smoothing, fuzzy derivative concept is also applied. This method provides better input for further image processing techniques. It also increases the contrast of the images, fine details and sharpening the edges as well. This comparative study, is made by numerical measures and visual inspection.

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Section: Resultsmentioning

confidence: 99%

“…This comparative study mainly aims at Gaussian Noise [1,2] which is also good at removing other Noises like Impulsive [3,4] and Multiplicative Noise [5]. Impulsive Noise consists of random occurrences of energy spikes having random amplitude and spectral content.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of Gaussian Noise Removal Methodologies for Gray Scale Images

Tulin¹

2017

IJCA

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“…There are different methods for impulse noise detection fuzzy approaches as in [10][11][12], neural approaches [13] and boundary based approaches [14][15][16][17][18]. Among the three categories, boundary based approach [14] is preferred due to its simplicity compared to computational complexity and system structure of other two categories.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Adaptive Weighted Switching Median Filter for Removing High Density Impulse Noise

Nair¹,

Mol²

2014

J. Inst. Eng. India Ser. B

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Restoration of images corrupted by impulse noise is a very active research area in image processing. In this paper, an Efficient Adaptive Weighted Switching Median filter for restoration of images that are corrupted by high density impulse noise is proposed. The filtering is performed as a two phase process-a detection phase followed by a filtering phase. In the proposed method, noise detection is done by HEIND algorithm proposed by Duan et al. The filtering algorithm is then applied to the pixels which are detected as noisy by the detection algorithm. All uncorrupted pixels in the image are left unchanged. The filtering window size is chosen adaptively depending on the local noise distribution around each corrupted pixels. Noisy pixels are replaced by a weighted median value of uncorrupted pixels in the filtering window. The weight value assigned to each uncorrupted pixels depends on its closeness to the central pixel.

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“…Various designs based on the concepts derived from the fuzzy sets theory combined with the order statistics have been also described [34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49]. Another family of techniques aimed at the improvement of the detail preservation of the filters based on reduced ordering is utilizing the concept of vector weighting, which privileges the central pixel of the processing window [50][51][52][53][54][55][56].…”

Section: Introductionmentioning

confidence: 99%

Adaptive rank weighted switching filter for impulsive noise removal in color images

Smołka

Malik

2012

J Real-Time Image Proc

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In this paper, a novel approach to the problem of impulsive noise removal in color digital images is presented. The described switching filter is based on the rank weighted, cumulated pixel dissimilarity measures, which are used for the detection of image samples contaminated by impulsive noise process. The introduced adaptive design enables the filter to tune its parameters to the amount of impulsive noise corrupting the image. The comparison with existing denoising schemes shows that the new technique more efficiently removes the impulses introduced by the noise process, while better preserving image details. An important feature of the new filter is its low computational complexity, which allows for its application in real-time applications.

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A fuzzy impulse noise detection and reduction method

Cited by 222 publications

References 17 publications

A Comparative Study of Gaussian Noise Removal Methodologies for Gray Scale Images

A Comparative Study of Gaussian Noise Removal Methodologies for Gray Scale Images

An Efficient Adaptive Weighted Switching Median Filter for Removing High Density Impulse Noise

Adaptive rank weighted switching filter for impulsive noise removal in color images

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