Title :
A new image feature point detection method based on Log-Gabor gradient feature
Author :
Jian Yang ; Zhongming Zhao
Author_Institution :
Inst. of Remote Sensing Applic., Chinese Acad. of Sci., Beijing, China
Abstract :
High spatial resolution remote sensing image automatic registration is one critical technologies in the imagery processing such as image mosaic, change detection and image fusion. The matching methods based on local characteristics, which applied in high-resolution remote sensing image registration, has the advantages of expressing more local image details, more strong anti-interference capability to the noise and the blocking. In the paper, we analyze the popular automatic registration methods and found the algorithm based on Log-Gabor gradient feature detector and descriptor, then finding the matching point pairs. In the search space we use the angle measure and the whole restrict parameters estimating method to match feature points, estimate image transformation model parameters, and finally achieve high-precision automatic registration results. Through data experiments, it shows that the methods is stable, reliable and more efficient than the traditional algorithms.
Keywords :
feature extraction; geophysical techniques; geophysics computing; image matching; image registration; remote sensing; Log-Gabor gradient feature descriptor; Log-Gabor gradient feature detector; anti-interference capability; change detection; high spatial resolution remote sensing; image automatic registration methods; image feature point detection method; image fusion; image mosaic; image transformation model parameters; imagery processing; matching point pairs; Band pass filters; Bandwidth; Computer vision; Detectors; Event detection; Gabor filters; Image registration; Image resolution; Remote sensing; Wavelet transforms; Auto Registration; Gradient Feature; Log-Gabor; Multi-Orientation; Multi-Scale;
Conference_Titel :
Urban Remote Sensing Event, 2009 Joint
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3460-2
Electronic_ISBN :
978-1-4244-3461-9
DOI :
10.1109/URS.2009.5137490