DocumentCode
86156
Title
A Robust SIFT Descriptor for Multispectral Images
Author
Saleem, Somaila ; Sablatnig, Robert
Author_Institution
Comput. Vision Lab., Vienna Univ. of Technol., Vienna, Austria
Volume
21
Issue
4
fYear
2014
fDate
Apr-14
Firstpage
400
Lastpage
403
Abstract
This letter presents a novel method for the description of multispectral image keypoints. The method proposed is based on a modified SIFT algorithm. It uses normalized gradients as local image features for the description of keypoints in order to achieve robustness against non linear intensity changes between multispectral images. The experimental results show that the method proposed achieves a better matching performance and outperforms the SIFT algorithm.
Keywords
Laplace transforms; image matching; Harris Laplace interest regions; local image features; multispectral image keypoints; nonlinear intensity change; normalized gradients; robust SIFT descriptor; Equations; Histograms; Indexes; Materials; Robustness; Signal processing algorithms; Visualization; Harris Laplace interest regions; image matching; multispectral images and SIFT;
fLanguage
English
Journal_Title
Signal Processing Letters, IEEE
Publisher
ieee
ISSN
1070-9908
Type
jour
DOI
10.1109/LSP.2014.2304073
Filename
6730675
Link To Document