Adaptive Smoothness Constraint Image Multilevel Fuzzy Enhancement Algorithm

We put forward a process of automatic airport extraction based on the characteristics of high resolution remote sensing images. First, through image enhancement algorithm, the contrast of target and background is enhanced. Second, we can extract the possible airport through the algorithms of Ostu segmentation, mathematical morphology corrosion and region-labeling. Finally, combined with the geometric structure of the runway, the airfield runway can be extracted through the algorithms of edge detection, progressive probability Hough transform and line connection. Then the possible airport can be verified by the extracted airfield runway. In the process, we proposed an improved fuzzy enhancement algorithm for image enhancement. This algorithm has good effect on the image enhancement and has strong robustness. The results of the experiment indicate that the process of automatic airport extraction is robust and has the advantages of high speed and degree of automation.

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A bilinear fast fuzzy enhancement algorithm for image boundary detection

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-169730 ◽

2018 ◽

Vol 35 (4) ◽

pp. 4083-4095

Author(s):

Qulin Tan ◽

Xiaopei Cai ◽

Xiaochun Qin ◽

Jiping Hu ◽

G. de Oliveira

Keyword(s):

Boundary Detection ◽

Fuzzy Enhancement ◽

Enhancement Algorithm

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Research on Improved Image Enhancement Algorithm Based on Fuzzy Set

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.605-607.2201 ◽

2012 ◽

Vol 605-607 ◽

pp. 2201-2205

Author(s):

Xi Wen Liu ◽

Chao Ying Liu

Keyword(s):

Image Enhancement ◽

Fuzzy Set ◽

Continuous Functions ◽

The Other ◽

Fuzzy Enhancement ◽

Good Ability ◽

Otsu Method ◽

Membership Grade ◽

Simulation Results ◽

Enhancement Algorithm

According to the shortcomings of the traditional fuzzy enhancement algorithms, several improvements are proposed. In this improved algorithm, the membership grade functions and fuzzy enhancement operator are made up of piecewise and continuous functions, the image is divided into two regions by OTSU method, one is high grey region, the other is low grey region, pixels in the high grey region are enhanced, and pixels in the low grey region are reduced. Simulation results show that this algorithm has good ability to enhance blur and little edges, and it is an effective and efficient way to increase image’s contrast.

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A New Method of Fundus Image Enhancement Based on Rough Set and Wavelet Transform

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.397-400.2205 ◽

2013 ◽

Vol 397-400 ◽

pp. 2205-2208

Author(s):

Wen Dong Zhao ◽

You Dong Zhang ◽

Chun Xia Jin

Keyword(s):

Wavelet Transform ◽

Image Enhancement ◽

Rough Set ◽

Fundus Images ◽

Fundus Image ◽

Visual Effects ◽

Multi Scale ◽

Fuzzy Enhancement ◽

Enhancement Algorithm ◽

Number Of Iterations

Fundus images are complex images with more details, and on the basis of the inadequate fuzzy enhancement algorithm proposed by Pal et al, this article propose an improved algorithm of rough set for fundus image enhancement. The fundus image will be multi-scale decomposed by wavelet transform firstly, and then the subgraphs are enhanced by using rough set to improve the visual effects; finally the processed sub-images will be reconstructed and generated a new-enhanced image. Compared with the Pal algorithm, the new algorithm not only overcomes its weaknesses that the threshold is set with a fixed value, but also reduces the number of iterations. Experimental results show that the improved enhancement algorithm has a better effect on the fundus image enhancement, and the various details of fundus images can be shown better.

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Enhancement of Eyeround Images Based on an Improved Fuzzy Algorithm

Journal of Advanced Computational Intelligence and Intelligent Informatics ◽

10.20965/jaciii.1999.p0441 ◽

1999 ◽

Vol 3 (6) ◽

pp. 441-445

Author(s):

Yaming Wang ◽

◽

Jiajun Wang ◽

Yuanmei Wang ◽

Yude Dong ◽

...

Keyword(s):

Image Quality ◽

Processing Speed ◽

Information Loss ◽

Fuzzy Algorithm ◽

Fuzzy Enhancement ◽

Enhancement Algorithm

Eye ground images are complex, with many details and uncertainties. Conventional enhancement algorithms do not enhance these images suitably of inferior processing. S. K. Pal proposed a fuzzy enhancement algorithm with advantages, but these were compromised by slow processing and information loss. We propose a fuzzy enhancement algorithm for eyeground images introducing mapping and implementing the algorithm through table searches, significantly improving image quality and processing speed.

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