期刊
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
卷 40, 期 12, 页码 2687-2691出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/tgrs.2002.807001
关键词
image segmentation; lacunarity; synthetic aperture radar (SAR); texture analysis
Based on the relative differential box-counting algorithm and the gliding-box algorithm, a novel,method for estimating the lacunarity features of grayscale digital images is proposed in this paper. Four nature texture images are used to test the performance of the novel lacunarity measure. Comparisons with published methods show that the proposed method can efficiently describe texture images, and provide accurate classification results. Real synthetic aperture radar (SAR) images analyses are found to have different lacunarity values for different regions. We show that good result can be obtained with appropriate lacunarity parameters applied to SAR images segmentation.
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