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Proceedings ArticleDOI

Fuzzy Filters for Noise Reduction: The Case of Gaussian Noise

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TLDR
Questions for images that are corrupted with Gaussian noise are answered for fuzzy inspired filters and there is a difference between numerical and visual results.
Abstract
Noise reduction is a well-known problem in image processing The reduction of noise in an image sometimes is as a goal itself, and sometimes is considered as a pre-processing step Besides the classical filters for noise reduction, quite a lot of fuzzy inspired filters have been proposed during the past years However, it is very difficult to judge the quality of this wide variety of filters For which noise types are they designed? How do they perform for those noise types? How do they perform compared to each other? Can we select filters that clearly outperform the others? Is there a difference between numerical and visual results? In this paper, we answer these questions for images that are corrupted with Gaussian noise

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Citations
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Journal ArticleDOI

A Fuzzy Noise Reduction Method for Color Images

TL;DR: A new fuzzy filter is presented for the reduction of additive noise for digital color images and the performance of the proposed method as preprocessing step for edge detection is illustrated.
Journal Article

A brief study of various noise model and filtering techniques

TL;DR: In image processing, noise reduction and restoration of image is expected to improve the qualitative inspection of an image and the performance criteria of quantitative image analysis techniques.
Journal ArticleDOI

Membership function construction for interval-valued fuzzy sets with application to Gaussian noise reduction

TL;DR: A novel method for the generation of membership functions, based on image histogram, to remedy that drawback of interval-valued fuzzy sets, and it complements the previous study.
Journal ArticleDOI

Additive noise removal using a novel fuzzy-based filter

TL;DR: A new fuzzy-based two-step filter for restoring images corrupted with additive noise reduction by reducing the noise in the color component differences without destroying the fine details of the image.
Proceedings ArticleDOI

Real-Time Lane Detection and Tracking for Advanced Driver Assistance Systems

TL;DR: The proposed algorithm is a combination of two sub-algorithms that aims to detect lane in normal as well as challenging scenarios by applying the concept of Hough Transform (HT) with a capable region of interest.
References
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Journal ArticleDOI

Noise reduction by fuzzy image filtering

TL;DR: A new fuzzy filter is presented for the noise reduction of images corrupted with additive noise, based on fuzzy rules which make use of membership functions.
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.
Journal ArticleDOI

Median filter based on fuzzy rules and its application to image restoration

TL;DR: A novel median-type filter controlled by fuzzy rules is proposed in order to remove impulsive noises on signals such as images, and the weight is set based on fuzzy rules concerning the states of the input signal sequence.
Journal ArticleDOI

Weighted fuzzy mean filters for image processing

TL;DR: A new fuzzy filter for the removal of heavy additive impulse noise, called the weighted fuzzy mean (WFM) filter, is proposed and analyzed in this paper.
Journal ArticleDOI

FIRE operators for image processing

TL;DR: A new family of filters for images corrupted by impulse noise and a new class of noise-protected operators for edge detection that perform significantly better than other techniques in the literature are presented.
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