A novel semiblind defocused image deconvolution technique is proposed, which is based on multivariate local polynomial regression MLPR and iterative Wiener filtering IWF . In this technique, firstly a multivariate local polynomial regression model is trained in wavelet domain to estimate defocus parameter. After obtaining the point spread function PSF parameter, iterative wiener filter is adopt...

The paper presents a novel method for joint blur identification and edge-driven image restoration in variational double regularized Bayesian estimation. The motivation is that the degradation of images includes not only additive, random noises but also multiplicative, spatial degradations, i.e., blur. Traditional nonlinear filtering techniques are observed in underutilization of blur identifica...

Amethod fully utilizing multiscale line filter responses is presented to estimate the point spread function (PSF) of a CT scanner and diameters of small tubular structures based on the PSF. The estimation problem is formulated as a least square fitting of a sequence of multiscale responses obtained at each medial axis point to the precomputed multiscale response curve for the ideal line model. ...

In most digital cameras, and even in high-end digital single lens reflex cameras, the acquired images are sampled at rates below the Nyquist critical rate, causing aliasing effects. This work introduces an algorithm for the subpixel estimation of the point spread function of a digital camera from aliased photographs. The numerical procedure simply uses two fronto-parallel photographs of any pla...

This paper tackles the problem of image deconvolution with joint estimation of point spread function (PSF) parameters and hyperparameters. Within a Bayesian framework, the solution is inferred via a global a posteriori law for unknown parameters and object. The estimate is chosen as the posterior mean, numerically calculated by means of a Monte Carlo Markov chain algorithm. The estimates are ef...

In weak lensing investigations, galaxy shapes are corrected for the convolution by the point spread function (PSF) using stellar images. In this paper we use physical models of the telescope optics to understand the spatial variation of the PSF in the image plane. We introduce a set of parameters to model the key aberrations, which include defocus, focal plane tilt, primary and off-axis astigma...

Accurate knowledge of the telescope’s point spread function (PSF) is essential for the weak gravitational lensing measurements that hold great promise for cosmological constraints. For space telescopes, the PSF may vary with time due to thermal drifts in the telescope structure, and/or due to jitter in the spacecraft pointing (ground-based telescopes have additional sources of variation). We de...

photocatalytic membranes exhibit great potential for water treatment since they combine the filtration and photo degradation in a single unit. although blending photocatalytic nanoparticles into polymeric thin film remains the simplest method to prepare the photocatalytic membrane, the entrapped photocatalyst showed less catalytic activity due to the agglomeration and shielding effects in the p...

1047-3203/$ see front matter 2011 Elsevier Inc. A doi:10.1016/j.jvcir.2011.07.010 ⇑ Corresponding author. E-mail addresses: [email protected] (J.-H. Lee Non-blind image deconvolution is a process that obtains a sharp latent image from a blurred image when a point spread function (PSF) is known. However, ringing and noise amplification are inevitable artifacts in image deconvolution since p...

A near accurate method for extracting blur parameters from a non-uniformly motion blurred images; in a blind image deconvolution scheme is proposed. In case of a non-uniform motion blur, we should be able to extract both the blur parameters and the combination of their extent fairly accurate, in order to improve the quality of the restored image. Initially, the parameters of the motion blur poi...