An automatic remote sensing mosaic algorithm based on modified SIFT feature

Zhong Chen; He Deng; GuoYou Wang

doi:10.1117/12.832642

30 October 2009 An automatic remote sensing mosaic algorithm based on modified SIFT feature

Zhong Chen, He Deng, GuoYou Wang

Proceedings Volume 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications; 74981E (2009) https://doi.org/10.1117/12.832642
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

Image mosaic technology is an important research field of image processing and a research focus on the computer vision and computer graphics. The traditional method is to select the feature points by manual selection method, which faces the problem of low reliability and efficiency in the batch of the image mosaic. The SIFT features have many properties that make them suitable for matching differing images of an object or scene. But the computation amount and the computation complexity are so great, which restricts the further real time application. So an automatic remote sensing image mosaic algorithm based on modified SIFT feature is presented in this paper to solve these problems. The method presented in this paper consisted of three steps: noise removal, modified SIFT feature registration and automatic mosaic. The test results show the modified mosaic algorithm based on the SIFT feature can improve the matching accuracy and reduce the computation times.

Citation Download Citation

Zhong Chen, He Deng, and GuoYou Wang "An automatic remote sensing mosaic algorithm based on modified SIFT feature", Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74981E (30 October 2009); https://doi.org/10.1117/12.832642

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available