We provide an IDL implementation of Fourier deconvolution and apply it to data from a WFC3 H1RG near-infrared array detector that exhibits inter-pixel capacitance (IPC). The deconvolution removes the most obvious deleterious effect of IPC: the cross-like pattern (i.e. the arithematic symbol for addition, “+”) of charge around pixels with large dark current, a.k.a. “hot” pixels. We also exhibit ...

To reduce the influence of atmospheric turbulence on images of space-based objects we are developing a maximum a posteriori deconvolution approach. In contrast to techniques found in the literature, we are focusing on the statistics of the point-spread function (PSF) instead of the object. We incorporated statistical information about the PSF into multi-frame blind deconvolution. Theoretical co...

Sedarat, Franklin, Eric Lin, Edwin D. W. Moore, and Glen F. Tibbits. Deconvolution of confocal images of dihydropyridine and ryanodine receptors in developing cardiomyocytes. J Appl Physiol 97: 1098 –1103, 2004. First published April 2, 2004; 10.1152/ japplphysiol.00089.2004.—Colocalization of dihydropyridine (DHPR) and ryanodine (RyR) receptors, a key determinant of Ca induced Ca release, was ...

Image deconvolution is a challenging ill-posed problem when only partial information of the blur kernel is available. Certain regularization on sharp images has to be imposed to constrain the estimation of true images during the blind deconvolution process. Based on the observation that an image of sharp edges tends to minimize the ratio between the `1 norm and the `2 norm of its wavelet frame ...

By assuming the reflectivity series to be sparse rather than ”white”, we introduced the hybrid norm spiking deconvolution (Zhang, 2010). However one theoretical drawback of spiking deconvolution is that it assumes the source wavelet to be minimum-phase, which might not be true in practice. We propose a new formulation of spiking deconvolution with the hybrid solver that does not require such as...

An approach to multi-channel blind deconvolution is developed, which uses an adaptive filter that performs blind source separation in the Fourier space. The approach keeps (during the learning process) the same permutation and provides appropriate scaling of components for all frequency bins in the frequency space. Experiments verify a proper blind deconvolution of convolution mixtures of sources.

An approach to multi-channel blind deconvolution is developed, which uses an adaptive filter that performs blind source separation in the Fourier space. The approach keeps (during the learning process) the same permutation and provides appropriate scaling of components for all frequency bins in the frequency space. Experiments verify a proper blind deconvolution of convolution mixtures of sources.

Although confocal microscopes have considerably smaller contribution of out-of-focus light than widefield microscopes, the confocal images can still be enhanced mathematically if the optical and data acquisition effects are accounted for. For that, several deconvolution algorithms have been proposed. As a practical solution, maximum-likelihood algorithms with regularization have been used. Howe...

ABSTRACT We consider the problem of image deconvolution. We foccus on a Bayesian approach which consists of maximizing an energy obtained by a Markov Random Field modeling. MRFs are classically optimized by a MCMC sampler embedded into a simulated annealing scheme. In a previous work, we have shown that, in the context of image denoising, a diffusion process can outperform the MCMC approach in ...