期刊
IEEE ACCESS
卷 7, 期 -, 页码 43970-43978出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2019.2908282
关键词
Image change detection; mathematical morphology filter; K-means clustering; logarithmic transformation; synthetic aperture radar (SAR) image
资金
- International Cooperative Research and Personnel Training Projects of the Ministry of Education of the People's Republic of China [DICE2014-2029, 2016-2196]
Synthetic aperture radar (SAR) images have been applied in disaster monitoring and environmental monitoring. With the objective of reducing the effect of noise on SAR image change detection, this paper presents an approach based on mathematical morphology filtering and K-means clustering for SAR image change detection. First, the multiplicative noise in two SAR images is transformed into additive noise by a logarithmic transformation. Second, the two multitemporal SAR images are denoised by morphological filtering. Third, the mean ratio operator and subtraction operator are used to obtain two difference images. Median filtering is applied to the difference image based on a simple combination of the two difference images. Since an accurate statistical model for the difference image cannot be easily established, the results of change detection are clustered using the K-means algorithm. A comparison of the experimental approach with other algorithms shows that the proposed algorithm can decrease the detection time and improve the detection result.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据