Lacunarity as a texture measure for SAR imagery
作者:
G. M. HENEBRY,
H. J. H. KUX,
期刊:
International Journal of Remote Sensing
(Taylor Available online 1995)
卷期:
Volume 16,
issue 3
页码: 565-571
ISSN:0143-1161
年代: 1995
DOI:10.1080/01431169508954422
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
Lacunarity analysis is a simple technique for characterizing texture in binary images. Lacunarity quantifies deviation from translational invariance by describing the distribution of gaps within the image at multiple scales: the more lacunar an image, the more heterogeneous the spatial arrangement of gaps. For grey-level data, a series of binary images are formed through slicing the image histogram by quantiles. Characteristic decays of lacunarity as a function of window size permit scene object texture to be distinguished from speckle. Using a series of ERS-1 SAR images of the Brazilian Pantanal, we demonstrate how lacunarity functions can link image phenomenology with scene dynamics.
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