You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither SPIE nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the SPIE website.
16 December 1992Image reconstruction using higher order statistics information
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.
Jun Liu andBoon-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
The alert did not successfully save. Please try again later.
Jun Liu, 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