New estimation of Hurst parameter for texture analysis

Yan Li; Jiaxiong Peng

doi:10.1117/12.441462

21 September 2001 New estimation of Hurst parameter for texture analysis

Yan Li, Jiaxiong Peng

Proceedings Volume 4550, Image Extraction, Segmentation, and Recognition; (2001) https://doi.org/10.1117/12.441462
Event: Multispectral Image Processing and Pattern Recognition, 2001, Wuhan, China

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.

Citation Download Citation

Yan Li and Jiaxiong Peng "New estimation of Hurst parameter for texture analysis", Proc. SPIE 4550, Image Extraction, Segmentation, and Recognition, (21 September 2001); https://doi.org/10.1117/12.441462

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