Please use this identifier to cite or link to this item:
http://hdl.handle.net/2080/726
Title: | Cloud Removal from Satellite Images Using Auto Associative Neural Network and Stationary Wevlet Transform |
Authors: | Sahoo, T Patnaik, S |
Keywords: | correlation methods image fusion neural nets principal component analysis wavelet transforms |
Issue Date: | 2008 |
Publisher: | IEEE |
Citation: | Proceedings of the first International Conference on Emerging Trends in Engineering and Technology, 2008. ICETET '08, Nagpur India, P 100-105 |
Abstract: | In this paper an image fusion technique is developed to remove clouds from satellite images. The proposed method involves an auto associative neural network based PCAT (principal component transform) and SWT (stationary wavelet transform) to remove clouds recursively which integrates complementary information to form a composite image from multitemporal images. Some evaluation measures are suggested and applied to compare our method with those of covariance based PCAT fusion method and WT-based one. The PSNR and the correlation coefficient value indicate that the performance of the proposed method is better than others. It also enhances the visual effect. |
Description: | Copyright for the paper belongs to IEEE |
URI: | http://dx.doi.org/ 10.1109/ICETET.2008.99 http://hdl.handle.net/2080/726 |
Appears in Collections: | Conference Papers |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
tsahoo.pdf | 1.24 MB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.