Scheduled System Maintenance:
On May 6th, single article purchases and IEEE account management will be unavailable from 8:00 AM - 12:00 PM ET (12:00 - 16:00 UTC). We apologize for the inconvenience.
By Topic

A new denoising method of SAR images in curvelet domain

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Yuan Guo ; Sch. of Inf. Sci. & Eng., Yunnan Univ., Kunming ; Zhengyao Bai

In this paper a new method of speckle reduction of SAR images in curvelet domain is proposed. In the method, curvelet transform is integrated with wavelet filtering. The new method consists of five parts: preprocessing, curvelet transform (CT), curvelet coefficients processing and two inverse transforms. In the preprocessing step, homomorphic transform is applied to convert multiplicative noise in SAR images to an additive noise which is suitable to be dealt with curvelets. After curvelet transform, curvelet coefficients are thresholded by using soft and hard thresholding functions with improved rules. In hard thresholding rule, noise variations are obtained by using noise parameter estimation. In soft thresholding rule, a classic soft thresholding function and thresholding rule used in wavelet domain is combined with curvelets. Finally, inverse CT and exponential transform are employed to reconstruct denoising image. Comparisons of speckle removing results by using different thresholding methods are also given in this paper. It can be seen that the method presented in the paper is an effective one.

Published in:

Control, Automation, Robotics and Vision, 2008. ICARCV 2008. 10th International Conference on

Date of Conference:

17-20 Dec. 2008