DocumentCode :
231773
Title :
Automatic multiband SAR image registration using sparse-based despeckling and Affine Scale Invariant transfrom
Author :
Sun Xiaohui ; Yu Qiuze ; Zhang Yan ; Hua Sunni
Author_Institution :
No. 38 Res. Inst., China Electron. Technol. Group Corp., Beijing, China
fYear :
2014
fDate :
19-23 Oct. 2014
Firstpage :
1090
Lastpage :
1093
Abstract :
A new method of automatic multiband SAR image registration based on Affine Scale Invariant and sparse-based despeckling is proposed. It first employs the sparse representation-based despeckling method to erase affection of speckle noise on image registration. Second, Normalized gradient feature space is designed to cope with affection of different grey value brought multiband SAR. Affine scale invariant transformation (Affine SIFT) is adopted to extract invariant feature and match them; RANSAC model is adopted to exclude the mismatched points. The image transformation model and parameter estimation using the rule of least root mean square error (RMSE) are discussed. The method is accurate, robust, and fast and has been tested on a lot of images. Experimental results using real multiband SAR images demonstrate the proposed method can achieve impressive results.
Keywords :
affine transforms; image registration; image representation; mean square error methods; parameter estimation; radar imaging; synthetic aperture radar; RANSAC model; RMSE; affine scale invariant transform; afine SIFT; automatic multiband SAR image registration; grey value; image transformation model; least root mean square error; normalized gradient feature space; parameter estimation; sparse representaion-based despeckling method; Abstracts; Deformable models; Educational institutions; Image edge detection; Image representation; Imaging; Sun; RANSAC-based consistency checking; automatic multiband SAR image registration; sparse representation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing (ICSP), 2014 12th International Conference on
Conference_Location :
Hangzhou
ISSN :
2164-5221
Print_ISBN :
978-1-4799-2188-1
Type :
conf
DOI :
10.1109/ICOSP.2014.7015171
Filename :
7015171
Link To Document :
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