Combining gray level and gradient magnitude for scene matching

Jiawei Wu; Chunfeng Wu; Nong Sang

doi:10.1117/12.830712

30 October 2009 Combining gray level and gradient magnitude for scene matching

Jiawei Wu, Chunfeng Wu, Nong Sang

Proceedings Volume 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis; 74952P (2009) https://doi.org/10.1117/12.830712
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

A correlation algorithm for scene matching by using two intensity features, i.e., gray level and gradient magnitude, is proposed. The correlation surface produced by the algorithm is the simple summation of the two ones obtained by using gray level and gradient magnitude respectively with zero mean normalized cross correlation similarity measure. We show that theoretically the proposed method will give better matching performance compared to the correlation algorithm by either gray level or gradient magnitude only under some conditions. Experimental results with real images demonstrate that the new algorithm can even report better results than classical algorithms and some newly presented ones.

Citation Download Citation

Jiawei Wu, Chunfeng Wu, and Nong Sang "Combining gray level and gradient magnitude for scene matching", Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 74952P (30 October 2009); https://doi.org/10.1117/12.830712

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