For exposure durations longer than about 40 msec, a field of dots in sampled motion has been reported to appear less smeared than predicted from the visual persistence of static displays. This reduction of perceived smear has been attributed to a motion "deblurring" mechanism. However, it has been long recognized that an isolated target moving continuously in a dark field appears to be extensiv...

This paper is concerned with deblurring and spectral analysis of ground-based astronomical images of space objects. A numerical approach is provided for deblurring and sparse unmixing of ground-based hyperspectral images (HSI) of objects taken through atmospheric turbulence. Hyperspectral imaging systems capture a 3D datacube (tensor) containing: 2D spatial information, and 1D spectral informat...

nonlinear diffusion filtering, deblurring, denoising An implicit, one-step method for the restoration of blurred and noisy color images is presented. Using a nonlinear partial differential equation (PDE)-based variational restoration approach, it is shown that a single iteration yields a result that is visually superior to performing Gaussian low-pass filtering, followed up by unsharp masking, ...

Image deblurring or signal restoration can be formulated as a data fitting least squares problem, but the problem is found to be ill-posed and regularization is needed, hence introducing the need to find a regularization parameter. We study the properties of the regularized least squares functional ‖Ax− b‖2Wb + ‖D(x− x0)‖ 2 Wx for the solution of discretely ill-posed systems of equations. It wa...

Blind image deblurring is a particularly challenging inverse problem where the blur kernel is unknown and must be estimated en route to recover the deblurred image. The problem is of strong practical relevance since many imaging devices such as cellphone cameras, must rely on deblurring algorithms to yield satisfactory image quality. Despite significant research effort, handling large motions r...

Over the last decade, a number of Computational Imaging (CI) systems have been proposed for tasks such as motion deblurring, defocus deblurring and multispectral imaging. These techniques increase the amount of light reaching the sensor via multiplexing and then undo the deleterious effects of multiplexing by appropriate reconstruction algorithms. However, a detailed analysis of CI has proven t...

Medical image acquisition devices are susceptible to producing blurry images due respiratory and patient movement. Despite having a notable impact on such blind-motion deblurring, medical deblurring is still underexposed. This study proposes an end-to-end scale-recurrent deep network learn the from multi-modal images. The proposed comprises novel residual dense block with spatial-asymmetric att...

Real images usually have sparse approximations under some tight frame systems derived from either framelets, over sampled discrete (window) cosine or Fourier transform. In this paper, we propose a method for image deblurring in tight frame domains. It is reduced to finding a sparse solution of a system of linear equations whose coefficients matrix is rectangular. Then, a modified version of the...

This paper presents a technique for deblurring noisy images. It includes two processing blocks, one for denoising and another for blind image restoration. The denoising step is based on the theories of singular value decomposition and compression-based filtering. The deblurring step is based on a double-regularization technique. Experimental results show that the combination of these techniques...

Lateral crosstalk in CMOS imaging arrays deter effective utilization of small pixel sizes (e.g., 5 0 m 5 0 m) now permitted by technology scaling. A simple measurement setup for empirical characterization of lateral crosstalk in CMOS image sensors is presented. A demonstration of deblurring operations based on the obtained blur model of lateral crosstalk is also provided. Several well-known lin...