Title :
IR remote sensing image registration based on multi-scale feature extraction
Author :
Jun Kong ; Min Jiang ; Yi-Ning Sun
Author_Institution :
Key Lab. of Adv. Process Control for Light Ind., Jiangnan Univ., Wuxi, China
Abstract :
Infrared remote sensing image has poor contrast and lower SNR so that real-time and robustness are not superior in image registration. In order to solve it, a novel registration based on Multi-scale feature extraction is proposed in this paper. This algorithm is designed in two aspects. Firstly, Gaussian convolution template size adjusts adaptively with the increasing of scale factors. Then the Multi-space is reconstructed. Secondly, feature points bidirectional matching based on the City-block distance is introduced into image registration. So the real-time performance and robustness are enhanced further. Finally, the experimental results showed that by this improved algorithm the infrared remote sensing images are registered more quickly and accurately than by traditional SIFT algorithm.
Keywords :
feature extraction; geophysical image processing; image matching; image reconstruction; image registration; infrared imaging; remote sensing; Gaussian convolution template size; IR remote sensing image registration; SIFT algorithm; SNR; city-block distance; feature points bidirectional matching; infrared remote sensing; multiscale feature extraction; multispace reconstruction; scale factors; scale-invariant feature transform; signal-to-noise ratio; Feature extraction; Image reconstruction; Image registration; Real-time systems; Remote sensing; Robustness; Vectors; IR remote sensing image; Multi-scale; feature points; registration;
Conference_Titel :
Neural Networks (IJCNN), 2014 International Joint Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6627-1
DOI :
10.1109/IJCNN.2014.6889630