Path: Top -> Journal -> Telkomnika -> 2015 -> Vol 13, No 1: March

Color Image Enhancement Based on Ant Colony Optimization Algorithm

Color Image Enhancement Based on Ant Colony Optimization Algorithm

Journal from gdlhub / 2016-11-09 12:32:16
Oleh : Haibo Gao, Wenjuan Zeng, Telkomnika
Dibuat : 2015-03-01, dengan 1 file

Keyword : ant colony optimization, weighted vector median filter, image enhancement
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/1274

In the collection, transmission, decoding process, the images are likely to produce noise. Noise makes the image color distorted and the articulation dropped, and also affects the image quality. Due to different causes, there are different types of noise, and the impulse noise is most common among them which exert great influence on the image quality. This paper, according to the characteristics of the color image, combines the ant colony algorithm and weighted vector median filter method to put forward an algorithm for the impulse noise removal and the color image enhancement. This method finds the optimal filter bank parameter by ant colony optimization (ACO) and processes image points polluted by the noise to achieve the purpose of image enhancement and protect the image details and edge information. Simulation experiment proves the correctness and validity of this method.

Deskripsi Alternatif :

In the collection, transmission, decoding process, the images are likely to produce noise. Noise makes the image color distorted and the articulation dropped, and also affects the image quality. Due to different causes, there are different types of noise, and the impulse noise is most common among them which exert great influence on the image quality. This paper, according to the characteristics of the color image, combines the ant colony algorithm and weighted vector median filter method to put forward an algorithm for the impulse noise removal and the color image enhancement. This method finds the optimal filter bank parameter by ant colony optimization (ACO) and processes image points polluted by the noise to achieve the purpose of image enhancement and protect the image details and edge information. Simulation experiment proves the correctness and validity of this method.

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