A New Estimation of Hurst Parameter for Texture Analysis

摘要

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.