Next Article in Journal
Effect of Tree Phenology on LiDAR Measurement of Mediterranean Forest Structure
Next Article in Special Issue
Online Hashing for Scalable Remote Sensing Image Retrieval
Previous Article in Journal
Using Satellite Altimetry to Calibrate the Simulation of Typhoon Seth Storm Surge off Southeast China
Previous Article in Special Issue
Deep Salient Feature Based Anti-Noise Transfer Network for Scene Classification of Remote Sensing Imagery
Open AccessArticle

A Novel Affine and Contrast Invariant Descriptor for Infrared and Visible Image Registration

1
Xi’an Microelectronics Technology Institute, Xi’an 710068, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(4), 658; https://doi.org/10.3390/rs10040658
Received: 2 April 2018 / Revised: 15 April 2018 / Accepted: 19 April 2018 / Published: 23 April 2018
(This article belongs to the Special Issue Learning to Understand Remote Sensing Images)
Infrared and visible image registration is a very challenging task due to the large geometric changes and the significant contrast differences caused by the inconsistent capture conditions. To address this problem, this paper proposes a novel affine and contrast invariant descriptor called maximally stable phase congruency (MSPC), which integrates the affine invariant region extraction with the structural features of images organically. First, to achieve the contrast invariance and ensure the significance of features, we detect feature points using moment ranking analysis and extract structural features via merging phase congruency images in multiple orientations. Then, coarse neighborhoods centered on the feature points are obtained based on Log-Gabor filter responses over scales and orientations. Subsequently, the affine invariant regions of feature points are determined by using maximally stable extremal regions. Finally, structural descriptors are constructed from those regions and the registration can be implemented according to the correspondence of the descriptors. The proposed method has been tested on various infrared and visible pairs acquired by different platforms. Experimental results demonstrate that our method outperforms several state-of-the-art methods in terms of robustness and precision with different image data and also show its effectiveness in the application of trajectory tracking. View Full-Text
Keywords: infrared image; image registration; MSER; phase congruency infrared image; image registration; MSER; phase congruency
Show Figures

Graphical abstract

MDPI and ACS Style

Liu, X.; Ai, Y.; Zhang, J.; Wang, Z. A Novel Affine and Contrast Invariant Descriptor for Infrared and Visible Image Registration. Remote Sens. 2018, 10, 658. https://doi.org/10.3390/rs10040658

AMA Style

Liu X, Ai Y, Zhang J, Wang Z. A Novel Affine and Contrast Invariant Descriptor for Infrared and Visible Image Registration. Remote Sensing. 2018; 10(4):658. https://doi.org/10.3390/rs10040658

Chicago/Turabian Style

Liu, Xiangzeng; Ai, Yunfeng; Zhang, Juli; Wang, Zhuping. 2018. "A Novel Affine and Contrast Invariant Descriptor for Infrared and Visible Image Registration" Remote Sens. 10, no. 4: 658. https://doi.org/10.3390/rs10040658

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop