NDLI: An improved Normalized Cross Correlation algorithm for SAR image registration

Content Provider	IEEE Xplore Digital Library
Author	Yufan Wang Qiuze Yu Wenxian Yu
Copyright Year	2012
Description	Author affiliation: Department of Electronic Engineering, Shanghai Jiao Tong University, China (Yufan Wang; Qiuze Yu; Wenxian Yu)
Abstract	This paper proposes a robust and fast matching method based on Normalized Cross Correlation (NCC) for Synthetic Aperture Radar (SAR) image matching. NCC is a robust algorithm in SAR image matching. Two main drawbacks of the NCC algorithm are the flatness of the similarity measure maxima, due to the self-similarity of the images, and the high computational complexity [1]. To tackle these two problems, we adopt the block partitioning strategy, texture feature analysis, and the Fast Fourier Transformation (FFT) algorithm and Integral Images to improve the performance of the conventional NCC algorithm. In the block partitioning strategy, we divide the template and the corresponding sub-window in the examined image into some sub-blocks, and there are several sub-blocks in the template, then we use texture features to increase the weight of sub-blocks which contain more terrain information in the template during the matching process, in this way we improve the flatness of the similarity measure maxima greatly. After that we use the FFT algorithm and Integral Images to speed up the proposed method, with the actual situation of our experiment we adopt the FFT and Integral Images based on the block partitioning strategy, thus we significantly reduce the number of computations required to carry out template matching based on the conventional NCC. Experimental results show that the proposed algorithm is more robust and faster than the conventional NCC algorithm.
Starting Page	2086
Ending Page	2089
File Size	485043
Page Count	4
File Format	PDF
ISBN	9781467311601
ISSN	21536996
e-ISBN	9781467311595
e-ISBN	9781467311588
DOI	10.1109/IGARSS.2012.6350961
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-22
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Partitioning algorithms Manganese Correlation Algorithm design and analysis Synthetic aperture radar Image resolution Texture Features Analysis Block Partitioning Strategy Fast Fourier Transformation (FFT)
Content Type	Text
Resource Type	Article

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