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Journal ArticleDOI

Salt-and-pepper noise detection and reduction using fuzzy switching median filter

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TLDR
This paper presents a new fuzzy switching median (FSM) filter employing fuzzy techniques in image processing that is able to remove salt-and-pepper noise in digital images while preserving image details and textures very well.
Abstract
This paper presents a new fuzzy switching median (FSM) filter employing fuzzy techniques in image processing. The proposed filter is able to remove salt-and-pepper noise in digital images while preserving image details and textures very well. By incorporating fuzzy reasoning in correcting the detected noisy pixel, the low complexity FSM filter is able to outperform some well known existing salt-and-pepper noise fuzzy and classical filters.

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Citations
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Journal ArticleDOI

Noise Adaptive Fuzzy Switching Median Filter for Salt-and-Pepper Noise Reduction

TL;DR: A novel two-stage noise adaptive fuzzy switching median (NAFSM) filter for salt-and-pepper noise detection and removal that employs fuzzy reasoning to handle uncertainty present in the extracted local information as introduced by noise.
Journal ArticleDOI

Fast and efficient median filter for removing 1-99% levels of salt-and-pepper noise in images

TL;DR: The proposed median filter restores corrupted images with 1-99% levels of salt-and-pepper impulse noise to satisfactory ones by intuitively and simply recognizing impulse noises, while keeping the others intact as nonnoises.
Journal ArticleDOI

An Efficient Adaptive Fuzzy Switching Weighted Mean Filter for Salt-and-Pepper Noise Removal

TL;DR: This letter proposes a novel adaptive fuzzy switching weighted mean filter to remove salt-and-pepper (SAP) noise and shows that compared to some state-of-the-art algorithms, it keeps more texture details and is better at removing SAP noise and depressing artifacts.
Journal ArticleDOI

Automatic screening and classification of diabetic retinopathy and maculopathy using fuzzy image processing

TL;DR: The paper highlights a novel online dataset and it presents the dataset collection, the expert diagnosis process and the advantages of the online database compared to other public eye fundus image databases for diabetic retinopathy purposes.
Journal ArticleDOI

Cluster-based adaptive fuzzy switching median filter for universal impulse noise reduction

TL;DR: Contrary to many existing filters that only focus on a particular impulse noise model, the proposed CAFSM filter is capable of filtering all kinds of impulse noise - the random-valued and/or fixed-valued impulse noise models.
References
More filters
Journal ArticleDOI

Detail-preserving median based filters in image processing

TL;DR: A switching scheme for median filtering which is suitable to be a prefilter before some subsequent processing e.g. edge detection or data compression is presented to remove impulse noises in digital images with small signal distortion.
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A new impulse detector for switching median filters

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.
Journal ArticleDOI

A new efficient approach for the removal of impulse noise from highly corrupted images

TL;DR: A new framework for removing impulse noise from images is presented in which the nature of the filtering operation is conditioned on a state variable defined as the output of a classifier that operates on the differences between the input pixel and the remaining rank-ordered pixels in a sliding window.
Journal ArticleDOI

Tri-state median filter for image denoising

TL;DR: A novel nonlinear filter, called tri-state median (TSM) filter, is proposed for preserving image details while effectively suppressing impulse noise by balancing the tradeoff between noise reduction and detail preservation.
Journal ArticleDOI

A fuzzy filter for images corrupted by impulse noise

TL;DR: A new operator is presented which adopts a fuzzy logic approach for the enhancement of images corrupted by impulse noise, and it is able to perform a very strong noise cancellation while preserving image details very well.
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