Please use this identifier to cite or link to this item: https://doi.org/10.1109/TGRS.2002.807001
Title: A novel lacunarity estimation method applied to SAR image segmentation
Authors: Du, G. 
Yeo, T.S. 
Keywords: Image segmentation
Lacunarity
Synthetic aperture radar (SAR)
Texture analysis
Issue Date: Dec-2002
Source: Du, G., Yeo, T.S. (2002-12). A novel lacunarity estimation method applied to SAR image segmentation. IEEE Transactions on Geoscience and Remote Sensing 40 (12) : 2687-2691. ScholarBank@NUS Repository. https://doi.org/10.1109/TGRS.2002.807001
Abstract: 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.
Source Title: IEEE Transactions on Geoscience and Remote Sensing
URI: http://scholarbank.nus.edu.sg/handle/10635/54618
ISSN: 01962892
DOI: 10.1109/TGRS.2002.807001
Appears in Collections:Staff Publications

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