A salient edges detection algorithm of multi-sensor images and its rapid calculation based on PFCM kernel clustering

1Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.

Abstract

Multi-sensor image matching based on salient edges has broad prospect in applications, but it is difficult to extract salient edges of real multi-sensor images with noises fast and accurately by using common algorithms. According to the analysis of the features of salient edges, a novel salient edges detection algorithm and its rapid calculation are proposed based on possibility fuzzy C-means (PFCM) kernel clustering using two-dimensional vectors composed of the values of gray and texture. PFCM clustering can overcome the shortcomings that fuzzy C-means (FCM) clustering is sensitive to noises and possibility C-means (PCM) clustering tends to find identical clusters. On this basis, a method is proposed to improve real-time performance by compressing data sets based on the idea of data reduction in the field of mathematical analysis. In addition, the idea that kernel-space is linearly separable is used to enhance robustness further. Experimental results show that this method extracts salient edges for real multi-sensor images with noises more accurately than the algorithm based on force fields and the FCM algorithm; and the proposed method is on average about 56 times faster than the PFCM algorithm in real time and has better robustness. © 2014 Production and hosting by Elsevier Ltd. on behalf of CSAA and BUAA.

Cite

CITATION STYLE

APA

Xu, G., Zhao, Y., Guo, R., Wang, B., Tian, Y., & Li, K. (2014). A salient edges detection algorithm of multi-sensor images and its rapid calculation based on PFCM kernel clustering. Chinese Journal of Aeronautics, 27(1), 102–109. https://doi.org/10.1016/j.cja.2013.12.001

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free