Recent advances in fuzzy techniques for image enhancement

Russo, F.

doi:10.1109/19.746707

Cited by 93 publications

(26 citation statements)

References 33 publications

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“…In the followings, the fuzzy edge detection method of Russo [4] is summarized. The idea of the method is very similar to that of the noise smoothing algorithms presented in Sect.…”

Section: Edge Detectionmentioning

confidence: 99%

“…There are many kinds of image properties to which certain methods are more or less sensitive [4]. It is also known that in most of the cases certain regions of images have different features while at the same time the parameters of the processing methods are usually functions of the image features.…”

Section: Introductionmentioning

confidence: 99%

“…As a result, the number of different approaches to evolutionary and fuzzy image processing has been progressively increasing (see e.g. [2][3][4]). …”

Section: Introductionmentioning

confidence: 99%

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New advances in digital image processing

Várkonyi-Kóczy

2010

Memetic Comp.

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Enhancement of noisy image data is a very challenging issue in many research and application areas. In the last few years, non-linear filters, feature extraction, high dynamic range imaging methods based on soft computing models have been shown to be very effective in removing noise without destroying the useful information contained in the image data. In this paper new image processing techniques are introduced in the above mentioned fields, thus contributing to the variety of advantageous possibilities to be applied. The main intentions of the presented algorithms are (1) to improve the quality of the image from the point of view of the aim of the processing, (2) to support the performance, and parallel with it (3) to decrease the complexity of further processing using the results of the image processing phase.

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“…In the followings, the fuzzy edge detection method of Russo [4] is summarized. The idea of the method is very similar to that of the noise smoothing algorithms presented in Sect.…”

Section: Edge Detectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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New advances in digital image processing

Várkonyi-Kóczy

2010

Memetic Comp.

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“…Among the recently developed processing techniques for imaging applications [1][2][3], the genetic algorithm [4,5] is considered an efficient inversion tool that can be use to extract features or elaborating the acquired images. In electromagnetic imaging, genetic algorithms (GAs) have been proposed for finding the global minimum of a given functional arising from the inverse scattering formulation [6].…”

Section: Introductionmentioning

confidence: 99%

Electromagnetic imaging of penetrable configurations by means of a GA/CG method

Caorsi¹,

Massa²,

Pastorino³

2004

Measurement

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“…As an intelligent computing technique, fuzzy logic has been widely used in various areas (de Carvalho and Costa 2007;Feng and Xu 1999;Gao et al 2008;John and Innocent 2005;Luo et al 2007;Zadeh et al 1975;Xu 1988;Xu 2006;Zhou and Gan 2007;Zhou and Xu 2001), in which fuzzy set and logic based intelligent signal/image processing has received increasingly attention (Pal and King 1981;Li and Yang 1989;Russo 1995Russo , 1998Farbiz et al 2000;Tyan and Wang 1993;Chen et al 1995;Plataniotis et al 1999;Xu 2000, 2002;Cheng and Li 2003;Cheng and Chen 1997;Cheng et al 1999). One strategy of applying fuzzy techniques to image processing is based on the operation of fuzzy membership functions using a fuzzy relaxation algorithm.…”

mentioning

confidence: 99%

Fuzziness index driven fuzzy relaxation algorithm and applications to image processing

Zhou

Gan

et al. 2008

Ann Oper Res

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An improved fuzzy relaxation algorithm for image contrast enhancement is introduced, the relationship between the convergence regions and the parameters in the transformations defined by the algorithm is shown, which is essential to the successful application of this algorithm. Furthermore, in order to measure the quality of an enhanced image, an index of fuzziness is used in this paper to evaluate the performance of the fuzzy relaxation scheme. This extended index of fuzziness is used as a criterion for automatically stopping the fuzzy relaxation process. The analytical result is tested by experiments of image contrast enhancement.

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Recent advances in fuzzy techniques for image enhancement

Cited by 93 publications

References 33 publications

New advances in digital image processing

New advances in digital image processing

Electromagnetic imaging of penetrable configurations by means of a GA/CG method

Fuzziness index driven fuzzy relaxation algorithm and applications to image processing

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