Aerial sequence image mosaic using reduced sift descriptors

Hongya Tuo; Zhongliang Jing; Tinghou Zhang

doi:10.1117/12.751054

15 November 2007 Aerial sequence image mosaic using reduced sift descriptors

Hongya Tuo, Zhongliang Jing, Tinghou Zhang

Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 67862V (2007) https://doi.org/10.1117/12.751054
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

Sequence image mosaic is an important and effective method to build a large "panoramic" scene which includes two main steps: image registration and intensity blending. In this paper, SIFT feature points are used to match images. SIFT are invariant to rotation, translation and scale changes, but the significant drawback is the high dimensional feature descriptor which lead to the expensive computation. So reduced SIFT descriptors are proposed to increase the speed of image registration. Linear combination methods of the matching points' gray-values are used for intensity blending. The experiments show that our method is useful and has high registration accuracy.

Citation Download Citation

Hongya Tuo, Zhongliang Jing, and Tinghou Zhang "Aerial sequence image mosaic using reduced sift descriptors", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67862V (15 November 2007); https://doi.org/10.1117/12.751054

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