基于高阶统计谱分解的统一纹理模型谐波提取

Yong Huang, K. Chan, Zhong Huang
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引用次数: 4

摘要

考虑到纹理是由统一纹理模型中的两个正交分量(确定性分量和不确定性分量)组成,提出了一种基于高阶统计量(HOS)谱分解的谐波提取方法。该方法基于四阶累积量的对角线切片估计功率谱,即使对有噪声的图像也能很容易地提取谐波频率。仿真和实验结果表明,该方法对纹理的分解是有效的,并且优于传统的基于低阶统计量的纹理分解方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Harmonics extraction based on higher order statistics spectrum decomposition for a unified texture model
By considering a texture being composed of two orthogonal components in a unified texture model, the deterministic component and the indeterministic component, a method of harmonics extraction from a Higher Order Statistics (HOS) based spectral decomposition is developed. The method estimates the power spectrum based on the diagonal slice of the fourth-order cumulants From this spectrum, the harmonic frequencies can be easily extracted even for noisy images. The simulation and experimental results indicate that this method is effective for texture decomposition and performs better than the traditional lower order statistics based decomposition methods.
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