Blind deconvolution for spatial distribution of Kα emission from ultraintense laser-plasma interaction

Abstract

The spatial distributions of the Kα emission from foil targets irradiated with ultra-intensity laser pulses have been studied using the x-ray coded imaging technique. Due to the effect of hard x-ray background contamination, noise as well as imperfection of imaging system, it is hard to determine the PSF analytically or measure it experimentally. Therefore, we propose a blind deconvolution method to restore both the spatial distributions of the Kα emission and the system's PSF from the coded images based on the maximum-likelihood scheme. Experimental restoration results from penumbral imaging and ring coded imaging demonstrated that both the structure integrity and the rich detail information can be well preserved.

Radiography of a Kα X-ray source generated through ultrahigh picosecond laser–nanostructure target interaction

“…A similar guiding and collimating mechanism is also reported in Ref. [14]. In contrast, for the planar target, some previous published data under similar experimental conditions shows that the spot size of the K α source is about 5-10 times larger than the laser spot size [8] .…”

“…To measure the spot size of the K α source, we use coded imaging technology [14] . A single-photon counting X-ray CCD camera with 1340 pixels × 1300 pixels and a 50 μm thick tantalum code plate were contained in the imaging system.…”

“…The CCD was not operated under the single-photon counting mode in the imaging process. For deconvoluting original data, we develop a blind restoration algorithm [14] . Figure 3(b) is the deconvoluted result from Fig.…”

Blind deconvolution for astronomical spectrum extraction from two-dimensional multifiber spectrum images

“…To date, the blind deconvolution principle has been used in a variety of research studies [16][17][18], but it has not been used in spectroscopic extraction. In this paper, we present an algorithmic framework based on the blind deconvolution principle for the extraction of optical fiber spectroscopy.…”

Image Deconvolution by Means of Frequency Blur Invariant Concept

“…But in most cases, the PSF is unknown. Hence, in order to estimate the PSF and the original image, blind deconvolution technique is adopted [7–13]. The general model which is used for the observed blurred image, g ( x , y ) of a scene, f ( x , y ), is described by a convolution integral: $\begin{array}{c}g\left(x,y\right)=f\left(x,y\right)\otimes h\left(x,y\right)+n\left(x,y\right),\end{array}$ where h ( x , y ) and n ( x , y ) are the PSF kernel and random noise, respectively.…”