Resolution enhancement of imaging small-scale portions in a compactly supported function.

Collocation Method using Compactly Supported Radial Basis Function for Solving Volterra's Population Model

‎In this paper‎, ‎indirect collocation approach based on compactly supported radial basis function (CSRBF) is applied for solving Volterra's population model. The method reduces the solution of this problem to the solution of a system of algebraic equations‎. ‎Volterra's model is a non-linear integro-differential equation where the integral term represents the effect of toxin‎. ‎To solve the pr...

Design of Small Animal Computed Tomography Imaging for in vitro and in vivo Studies

Introduction: Mini Computed Tomography (mini-CT) was suggested in biomedical research to investigate tissues and small animals. We present designed and built a mini x-ray computed tomography (mini-CT) for small animals as well as industrial component imaging. Materials and Methods: The system used in this study includes a X-ray tube 20kV to 160kV and a flat pa...

A new approach to contrast enhancement in MAGICA gel dosimeter image with MRI technique

parameters that have to be measured in gel dosimetry. However, the resolution in gel is strongly dependant on gel composition. Selection of optimum method in dose response readout and proper values of parameters can result in noise reduction as well as improvement of contrast, and spatial resolution considerably. Materials and Methods: MAGICA polymer gel dosimeters were manufactured and irradia...

Construction of Compactly Supported Nonseparable Orthogonal Wavelets of L^2(R^n)

A Deep Model for Super-resolution Enhancement from a Single Image

This study presents a method to reconstruct a high-resolution image using a deep convolution neural network. We propose a deep model, entitled Deep Block Super Resolution (DBSR), by fusing the output features of a deep convolutional network and a shallow convolutional network. In this way, our model benefits from high frequency and low frequency features extracted from deep and shallow networks...