Paper Info
Title
BFSIFT: A Novel Method to Find Feature Matches for SAR Image Registration
Abstract
In this letter, we propose a novel method based on bilateral filter (BF) scale-invariant feature transform (SIFT) (BFSIFT) to find feature matches for synthetic aperture radar (SAR) image registration. First, the anisotropic scale space of the image is constructed using BFs. The constructing process is noniterative and fast. Compared with the Gaussian scale space used in SIFT, more accurately located matches can be found in the anisotropic one. Then, keypoints are detected and described in the coarser scales using SIFT. At last, dual-matching strategy and random sample consensus are used to establish matches. The probability of correct matching is significantly increased by skipping the finest scale and by the dual-matching strategy. Experiments on various slant range images demonstrate the applicability of BFSIFT to find feature matches for SAR image registration.
Year
DOI
Venue
2012
10.1109/LGRS.2011.2177437
IEEE Geosci. Remote Sensing Lett.
Keywords
Field
DocType
synthetic aperture radar,scale-invariant feature transform (sift),scale invariant feature transform,image matching,synthetic aperture radar (sar),anisotropic scale space (ass),synthetic aperture radar image registration,sar image registration,bilateral filter (bf),feature extraction,random sample,filtering theory,feature matching,anisotropic scale,dual matching strategy,radar imaging,bilateral filter,edge detection,image registration,random sampling,bilateral filtering,kernel,remote sensing,scale space
Scale-invariant feature transform,Synthetic aperture radar,Remote sensing,Scale space,Artificial intelligence,Bilateral filter,Computer vision,Radar imaging,Pattern recognition,Feature extraction,Mathematics,Slant range,Image registration
Journal
Volume
Issue
ISSN
9
4
1545-598X
Citations 
PageRank 
References 
34
1.47
14
Authors
3
Name
Order
Citations
PageRank
Shanhu Wang1341.47
Hongjian You210317.44
Kun Fu341457.81