Image reconstruction using higher order statistics information

Jun Liu; Boon-Hee Soong

doi:10.1117/12.130878

16 December 1992 Image reconstruction using higher order statistics information

Jun Liu, Boon-Hee Soong

Proceedings Volume 1766, Neural and Stochastic Methods in Image and Signal Processing; (1992) https://doi.org/10.1117/12.130878
Event: San Diego '92, 1992, San Diego, CA, United States

Abstract

The higher order cumulants and their Fourier transforms, polyspectra, are used in order to achieve a number of objects which may not be possible to obtain using second order statistics. In this paper, we study different approaches to estimate the bispectrum and apply the result to the image reconstruction and communication signal identification. One of the key advantages of using cumulants in the signal processing are is that cumulants are blind to all kinds of Gaussian processes. Thus, when a cumulants method is used on non-Gaussian signals polluted by additive Gaussian noise, it will improve the signal/noise ratio.

Citation Download Citation

Jun Liu and Boon-Hee Soong "Image reconstruction using higher order statistics information", Proc. SPIE 1766, Neural and Stochastic Methods in Image and Signal Processing, (16 December 1992); https://doi.org/10.1117/12.130878

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