Journal
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
Volume 40, Issue 12, Pages 2687-2691Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/tgrs.2002.807001
Keywords
image segmentation; lacunarity; synthetic aperture radar (SAR); texture analysis
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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.
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