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Proceedings Paper

Improved phase congruency based interest point detection for multispectral remote sensing images
Author(s): Min Chen; Qing Zhu; Jun Zhu; Zhu Xu; Duoxiang Cheng
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Paper Abstract

One of the biggest challenges in multispectral image interest point detection is the variation of radiation. Many methods have been proposed to address this problem. However, the detection performance is still unstable. In this paper, a robust point detector is proposed. Firstly, image illumination space is constructed by using a parameters adaptive method. Secondly, a phase congruency based interest point detection algorithm is adopted to compute candidate points in illumination space. Then, all interest point candidates are mapped back to the original image and a non-maximum suppression step is added to find final interest points. Finally, the feature scale values of all interest points are calculated based on the Laplacian function. The experimental results show that the proposed method performs better than other traditional methods in feature repeatability rate and repeated features number for multispectral images.

Paper Details

Date Published: 2 March 2016
PDF: 6 pages
Proc. SPIE 9901, 2nd ISPRS International Conference on Computer Vision in Remote Sensing (CVRS 2015), 990116 (2 March 2016); doi: 10.1117/12.2234947
Show Author Affiliations
Min Chen, Southwest Jiaotong Univ. (China)
Sichuan Engineering Research Ctr. for Emergency Mapping and Disaster Reduction (China)
Qing Zhu, Southwest Jiaotong Univ. (China)
Jun Zhu, Southwest Jiaotong Univ. (China)
Zhu Xu, Southwest Jiaotong Univ. (China)
Collaborative Innovation Ctr. for Rail Transport Safety (China)
Joint Engineering Lab. of Spatial Information Technology for High-speed Railway Safety (China)
Duoxiang Cheng, Sichuan Bureau of Surveying, Mapping and Geoinformation (China)


Published in SPIE Proceedings Vol. 9901:
2nd ISPRS International Conference on Computer Vision in Remote Sensing (CVRS 2015)
Cheng Wang; Rongrong Ji; Chenglu Wen, Editor(s)

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