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Recently, the type of compound regularizers has become a popular choice for signal reconstruction. The estimation quality is generally sensitive to the values of multiple regularization parameters. In this work, based on BDF algorithm, we develop a data-driven optimization scheme based on minimization of Stein's unbiased risk estimate (SURE)— statistically equivalent to mean squared error (MSE). We...
We propose an unbiased estimate of a filtered version of the mean squared error—the blur-SURE (Stein’s unbiased risk estimate)—as a novel criterion for estimating an unknown point spread function (PSF) from the degraded image only. The PSF is obtained by minimizing this new objective functional over a family of Wiener processings. Based on this estimated blur kernel, we then perform nonblind deconvolution...
We propose a generalized cross validation (GCV) as a novel criterion for estimating a point spread function (PSF) from the degraded image only. The PSF is obtained by minimizing this new objective functional over a family of Wiener processings. Based on this estimated PSF, we then perform deconvolution using our recently developed SURE-LET algorithm. The GCV-based criterion is exemplified with a number...
The Doppler frequency shift can make a mismatch in frequency band between the linear frequency modulation (LFM) signal and its matched filter. The amplitude and delay of the output pulse are based on the degree of the mismatch. An algorithm of Doppler frequency estimation is proposed basing on the amplitude of the output pulse. The algorithm sets a group of matched filters whose middle frequencies...
In this paper, we consider blind deconvolution that consists of PSF (point spread function) estimation and non-blind deconvolution. It has been proved that blur-SURE — a modified version of SURE (Stein's unbiased risk estimate) — is a valid criterion for parametric PSF estimation.
We propose a novel blind deconvolution method that consisting of firstly estimating the variance of the Gaussian blur, then performing non-blind deconvolution with the estimated PSF. The main contribution of this paper is the first step — to estimate the variance of the Gaussian blur, by minimizing a novel objective functional: an unbiased estimate of a blur MSE (SURE). The optimal parameter and blur...
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