We present a new algorithm for estimating the Point Spread Function (PSF) in wide-field astronomical images with extreme source crowding. Robust and accurate PSF estimation crowded dramatically improves fidelity of astrometric photometric measurements extracted from sky monitoring imagery. Our radically approach utilizes convolutional sparse representations to model continuous functions involve...

The precise knowledge of the point spread function is central for any imaging system characterization. In fluorescence microscopy, point spread function (PSF) determination has become a common and obligatory task for each new experimental device, mainly due to its strong dependence on acquisition conditions. During the last decade, algorithms have been developed for the precise calculation of t...

Context . Access to knowledge of the point spread function (PSF) adaptive optics(AO)-assisted observations is still a major limitation when processing AO data. This particularly important image analysis requires use deconvolution methods. As PSF complex and time-varying function, reference PSFs acquired on calibration stars before or after scientific observation can be too different from actual...

In this paper, we describe the procedures to make epoxy resin and agarose phantoms designed using Mie scattering calculations. The phantoms are constructed to be used in the estimation of point spread function (PSF) of an optical coherence tomography (OCT) and evaluation of optical properties extraction (OPE) algorithm.

Conclusions; We propose a fully digital auto-focusing system based on novel out-of-focus blur estimation and restoration algorithms. The main advantages of the proposed PSF estimation algorithm are that it can estimate both radius and sample values of an arbitrary circularly symmetric blur, and that it does not require the DFT or a numerical optimisation process for parameter estimation. As a r...

In this paper we present optimized algorithms for image deblurring in the case of a separable Point Spread Function (PSF). Our work is in the usual context of Bayesian estimation with Gibbs Random Fields (GRF). The derived algorithms fall into the class of Single Site Update Algorithms (SSUAs), which exhibit a high convergence rate per iteration [l] and small memory requirements, while hard dom...

Calibration of scanners and cameras usually involves measuring the point spread function (PSF). When edge data is used to measure the PSF, the differentiation step amplifies the noise. A parametric fit of the functional form of the edge spread function (ESF) directly to the measured edge data is proposed to eliminate this. Experiments used to test this method show that the Cauchy functional for...

We present a novel progressive framework for blind image restoration. Common blind restoration schemes first estimate the blur kernel, then employ non-blind deblurring. However, despite recent progress, the accuracy of PSF estimation is limited. Furthermore, the outcome of non-blind deblurring is highly sensitive to errors in the assumed PSF. Therefore, high quality blind deblurring has remaine...

A method has been proposed for blindly estimating the Point Spread Function (PSF) of video data. The PSF’s of the images in a sequence are assumed to be of compact support and hence admit FIR modeling. The zeros (roots) of the Optical Transfer Function (OTF) i.e. the Fourier transform of the PSF are first estimated by locating the singularities of the magnitude of the cross power spectrum. Thes...