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Harmonics Extraction Based on Higher Order Statistics Spectrum Decomposition for a Unified Texture Model

Yong Huang, Kap Luk Chan, ZhongYang Huang
ICCV 2001 pp. 245-250
doi:10.1109/ICCV.2001.937631 /iccv/2001/huang2001iccv-harmonics/

Abstract

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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Cite

Text

Huang et al. "Harmonics Extraction Based on Higher Order Statistics Spectrum Decomposition for a Unified Texture Model." IEEE/CVF International Conference on Computer Vision, 2001. doi:10.1109/ICCV.2001.937631

Markdown

[Huang et al. "Harmonics Extraction Based on Higher Order Statistics Spectrum Decomposition for a Unified Texture Model." IEEE/CVF International Conference on Computer Vision, 2001.](https://mlanthology.org/iccv/2001/huang2001iccv-harmonics/) doi:10.1109/ICCV.2001.937631

BibTeX

@inproceedings{huang2001iccv-harmonics,
  title     = {{Harmonics Extraction Based on Higher Order Statistics Spectrum Decomposition for a Unified Texture Model}},
  author    = {Huang, Yong and Chan, Kap Luk and Huang, ZhongYang},
  booktitle = {IEEE/CVF International Conference on Computer Vision},
  year      = {2001},
  pages     = {245-250},
  doi       = {10.1109/ICCV.2001.937631},
  url       = {https://mlanthology.org/iccv/2001/huang2001iccv-harmonics/}
}