A New Image Texture Segmentation Based on Contourlet Fractal Features

被引：6
|
作者：
Sarafrazi, Katayoon [1 ]
Yazdi, Mehran [1 ]
Abedini, Mohammad Javad [2 ]
机构：
[1] Shiraz Univ, Dept Commun & Elect, Shiraz, Iran
[2] Shiraz Univ, Dept Civil & Environm Engn, Shiraz, Iran
来源：
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING | 2013年 / 38卷 / 12期
关键词：
Texture segmentation; Fractal theory; Contourlet transform; Statistical features; Fuzzy features; Power spectrum features; MULTIFRACTAL ESTIMATION; CLASSIFICATION; DIMENSION;
D O I：
10.1007/s13369-013-0624-z
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
Texture segmentation is one of the most difficult and important tasks in the remote sensing image processing. Through the years, several methods, based on statistical features, structural features and other image features, have been proposed for texture segmentation. This paper proposes a new feature based on Contourlet transform and Fractal analysis for texture segmentation. The performance of the proposed feature is compared with that of fractal, statistical, fuzzy and power spectrum features in presence of noise and the obtained results show superiority of the new proposed feature.
引用
收藏
页码：3437 / 3449
页数：13
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