Isolating impulsive noise pixels in color images by peer group techniques

Morillas, Samuel; Gregori, Valentı́n; Perís-Fajarnés, Guillermo

doi:10.1016/j.cviu.2007.05.001

Cited by 59 publications

(42 citation statements)

References 29 publications

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“…For instance, the concepts of principal and strong fuzzy metric were motivated by the study of the p-convergence, [31], and the generalization of non-Archimedean fuzzy metrics, [44], respectively. Moreover, recently, fuzzy metrics have been applied to colour image filtering by replacing classical metrics and some improvements have been achieved [2,3,[34][35][36][37][38][39]. In this context, the presence of the t parameter is indeed a key issue because it allows the fuzzy metric to perform adaptively which is beneficial to improve performance.…”

Section: Introductionmentioning

confidence: 99%

Some questions in fuzzy metric spaces

Gregori

MiòAna

Morillas

2012

Fuzzy Sets and Systems

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ElsevierGregori Gregori, V.; Morillas Gómez, S.; Miñana Prats, JJ. (2012) AbstractThe George and Veeramani's fuzzy metric defined by M * (x, y, t) = min{x,y}+t max{x,y}+t on [0, ∞[ (the set of non-negative real numbers) has shown some advantages in front of classical metrics in the process of filtering images. In this paper we study from the mathematical point of view this fuzzy metric and other fuzzy metrics related to it. As a consequence of this study we introduce, throughout the paper, some questions relative to fuzzy metrics. Also, as another practical application, we show that this fuzzy metric is useful for measuring perceptual colour differences between colour samples.

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Section: Introductionmentioning

confidence: 99%

Some questions in fuzzy metric spaces

Gregori

MiòAna

Morillas

2012

Fuzzy Sets and Systems

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“…21 Comparison of the efficiency of the proposed switching technique with other denoising methods using a part of the color test image PEPPERS contaminated by NM3 with intensity p = 0.1 J Real-Time Image Proc (2015) 10:289-311 307 [22,66,68,[76][77][78], without the need for calculating the corresponding distances for all pixels in the window. The computational burden of the VMF-based approaches can be, however, simplified adopting simpler dissimilarity measures and applying some approximations [23,30,31,[104][105][106][107][108], which do not decrease significantly the noise filtering performance.…”

Section: Comparison With Existing Techniquesmentioning

confidence: 99%

“…In order to alleviate the problems caused by the blurring properties of the VMF and other filters utilizing the ordering scheme, a filtering method using the concept of a peer group was introduced in [71,72] and extensively used in various filtering designs [49,57,66,[73][74][75][76][77][78]. The peer group associated with the central pixel x i of a filtering window W i denotes the set of close pixels, whose distance to x i is not exceeding a given threshold.…”

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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“…An efficient family of filters is utilizing the concept of a peer group introduced in [5,11,41,42] and its fuzzy extensions [27,28], in which a combination of impulsive noise detection and a replacement scheme based on averaging is performed. Another group of filters relies on the concept of geodesic digital paths [8,25,26,51], which determines the connection cost between pixels belonging to the processing window used as weights in the averaging process.…”

Section: Introductionmentioning

confidence: 99%

Robust local similarity filter for the reduction of mixed Gaussian and impulsive noise in color digital images

Smołka

Kusnik

2015

SIViP

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In this paper, a novel technique designed for the suppression of mixed Gaussian and impulsive noise in color images is proposed. The new denoising scheme is based on a weighted averaging of pixels contained in a filtering block. The main novelty of the proposed solution lies in the new definition of the similarity between the samples of the processing block and a small window centered at the block's central pixel. Instead of direct comparison of pixels, a measure based on the similarity between a given pixel and the samples from the neighborhood of the central pixel is utilized. This measure is defined as the sum of distances in a given color space, between a pixel of the block and a certain number of most similar samples from the filtering window. The main advantage of the proposed scheme is that the new similarity measure is not influenced by the outliers injected into the image by the impulsive noise and the averaging process ensures the effectiveness of the new filter in the reduction of Gaussian noise. The experimental results prove that the novel filtering design is capable of suppressing mixed noise of high intensity and is competitive with respect to the stateof-the-art noise filtering methods.

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Isolating impulsive noise pixels in color images by peer group techniques

Cited by 59 publications

References 29 publications

Some questions in fuzzy metric spaces

Some questions in fuzzy metric spaces

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

Robust local similarity filter for the reduction of mixed Gaussian and impulsive noise in color digital images

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