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Proceedings Paper

New estimation of Hurst parameter for texture analysis
Author(s): Yan Li; Jiaxiong Peng
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Paper Abstract

A new algorithm to estimate Hurst parameter is introduced in this work. A remote sensing texture is modeled as a fBm process. Since fBm is characterized by only one Hurst parameter, it is not flexible enough to model the short-term correlation structure. Therefore extended models were proposed to settle this problem. Noting that the track of the logarithm delta variances is certain, and the slopes k(s) of the piecewise lines characterize the specific texture, we use k(s)/2 to estimate the multiscale Hurst parameters of the digital image. Since the new features characterize the textures in a multi-scale way and meet with the characters of the natural processes, they perform better than the existing features based on fractal models and wavelet transforms.

Paper Details

Date Published: 21 September 2001
PDF: 6 pages
Proc. SPIE 4550, Image Extraction, Segmentation, and Recognition, (21 September 2001); doi: 10.1117/12.441462
Show Author Affiliations
Yan Li, Huazhong Univ. of Science and Technology (China)
Jiaxiong Peng, Huazhong Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 4550:
Image Extraction, Segmentation, and Recognition
Tianxu Zhang; Bir Bhanu; Ning Shu, Editor(s)

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