Paper
30 September 1994 Blur identification based on higher order spectral nulls
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Abstract
The identification of the point spread function (PSF) from the degraded image data constitutes an important first step in image restoration that is known as blur identification. Though a number of blur identification algorithms have been developed in recent years, tow of the earlier methods based on the power spectrum and power cepstrum remain popular, because they are easy to implement and have proved to be effective in practical situations. Both methods are limited to PSF's which exhibit spectral nulls, such as due to defocused lens and linear motion blur. Another limitation of these methods is the degradation of their performance in the presence of observation noise. The central slice of the power bispectrum has been employed as an alternative to the power spectrum which can suppress the effects of additive Gaussian noise. In this paper, we utilize the bicepstrum for the identification of linear motion and defocus blurs. We present simulation results where the performance of the blur identification methods based on the spectrum, the cepstrum, the bispectrum and the bicepstrum is compared for different blur sizes and signal-to-noise ratio levels.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Andreas E. Savakis and Roger L. Easton Jr. "Blur identification based on higher order spectral nulls", Proc. SPIE 2302, Image Reconstruction and Restoration, (30 September 1994); https://doi.org/10.1117/12.188038
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Cited by 7 scholarly publications.
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KEYWORDS
Signal to noise ratio

Point spread functions

Image restoration

Algorithm development

Fourier transforms

Motion models

Signal processing

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