Image Denoising using Contourlet Transform

被引：4

作者：

Sivakumar, R. ^{[1
]}

Balaji, G. ^{[1
]}

Ravikiran, R. S. J. ^{[1
]}

Karikalan, R. ^{[1
]}

Janaki, S. Saraswathi ^{[1
]}

机构：

[1] RMK Engn Coll, ECE Dept, Kavaraipettai, Tamil Nadu, India

来源：

SECOND INTERNATIONAL CONFERENCE ON COMPUTER AND ELECTRICAL ENGINEERING, VOL 1, PROCEEDINGS | 2009年

关键词：

Denoising; Contourlet Transform; SNR;

D O I：

10.1109/ICCEE.2009.70

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In image processing, considering fields like remote sensing and medical applications, Speckle (Multiplicative) noise dominates which affects the valuable features and important information of the image. To denoise an image, various transforms are used. But they are not efficient in case of preserving the edges which is the important factor in image processing for Image denoising. In this paper we have used the new algorithm based on the transformation named 'Contourlet Transform'. This algorithm is more efficient than the wavelet algorithm in Image Denoising particularly for the removal of speckle noise. The parameters considered for comparing the wavelet and Contour let Transforms are SNR and IEF. The results show that this proposed algorithm outperforms the wavelet in terms of SNR, IEF values and visual perspective as well.

引用

页码：22 / 25

页数：4