A Comparative study between wavelet and Contourlet Transform Features for Textural Image Classification

被引：0

作者：

Javidan, Reza ^{[1
]}

Masnadi-Shirazi, M. A. ^{[2
]}

Azimifar, Z. ^{[3
]}

Sadreddini, M. H. ^{[3
]}

机构：

[1] Azad Univ Beyza, Dept Comp Engn, Beyza, Iran

[2] Shiraz Univ, Elect Engn Dept, Shiraz, Iran

[3] Shiraz Univ, Comp Engn Dept, Shiraz, Iran

来源：

2008 3RD INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGIES: FROM THEORY TO APPLICATIONS, VOLS 1-5 | 2008年

关键词：

seabed; contourlet transform; texture; classification; wavelet transform;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Contourlet transform is a new two-dimensional extension of the wavelet transforms using multiscale and directional filter banks. In this paper, the effectiveness of the features obtained from the contourlet transform is investigated and is compared with the wavelet transform features for image texture classification. We specially focused on image acquisition conditions that an image from one scene may be acquired with different illumination, scale, direction, distance and slope. It is shown that the accuracy of the contourlet transform features in such conditions is more than that of the wavelet transform. However, wavelet transform is still applicable in many texture classification tasks.

引用

页码：971 / +

页数：3

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