New least-squares minimum error variance deconvolution method

Mostafa Abdelhakam Ibrahim; Abdel-Wahab F. Hussein; Samia A. Mashali; Ahmed H. Mohamed

doi:10.1117/12.323208

1 October 1998 New least-squares minimum error variance deconvolution method

Mostafa Abdelhakam Ibrahim, Abdel-Wahab F. Hussein, Samia A. Mashali, Ahmed H. Mohamed

Proceedings Volume 3460, Applications of Digital Image Processing XXI; (1998) https://doi.org/10.1117/12.323208
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1998, San Diego, CA, United States

Abstract

We propose to minimize a cost function, which depends on the values of the input signal to a linear time-invariant system, to reach an optimal estimation of this input signal. This cost function is the square of the error signal between the output and the convolution of the estimated input with the blurring system. The minimization of the cost function is done using an optimization technique which requires the use of an initial estimation of the input signal. Van- Cittert deconvolution method gives this required initial estimation. Singular value decomposition technique is used in estimating the improved input signal.

Citation Download Citation

Mostafa Abdelhakam Ibrahim, Abdel-Wahab F. Hussein, Samia A. Mashali, and Ahmed H. Mohamed "New least-squares minimum error variance deconvolution method", Proc. SPIE 3460, Applications of Digital Image Processing XXI, (1 October 1998); https://doi.org/10.1117/12.323208

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