A FUZZY AFFINITY PROPAGATION CLASSIFICATION FOR HYPERSPECTRAL REMOTELY SENSED IMAGES
(0) Due to the improvement of remote sensing instruments, hyperspectral sensors can collect hundreds of channels simultaneously compares to multispectral imagery usually with less than ten channels. How to process this huge amount of data is a challenge problem, especially when the spectra of the land-covers are unavailable. In this study, we propose a fuzzy affinity propagation method for image classification. Affinity propagation is a clustering algorithm has fast execution speed and finds clusters with small error. Different distance measures can be used to estimate of how closely two pixel vectors resemble each other. After the affinity propagation clustering, a fuzzy classification is applied for soft classification based on the distance of every pixel vectors to each cluster. An AVIRIS image scene is adopted in experiment to demonstrate the capability of the proposed method.
Affinity propagation (AP) fuzzy classification unsupervised classification.
Cheng-Chun Dai Hsuan Ren
Science Program in Remote Sensing Science and Technology,National Central University, No.300, Jhongd Center for Space and Remote Sensing Research, National Central University, No.300, Jhongda Rd., Jhon
国内会议
哈尔滨
英文
1-4
2011-08-01（万方平台首次上网日期，不代表论文的发表时间）