Microscopic images are becoming important and need to be studied know the details how-to quantitatively evaluate decellularization. Most of existing research focuses on deep learning-based techniques that lack simplification for A new computational method segmentation microscopy based shearlet neural network (SNN) has been introduced. The proposal is link concept shearlets transform networks in...

Fourier Integral Operators appear naturally in a variety of problems related to hyperbolic partial differential equations. While wavelets and other traditional time-frequency methods have been successfully employed for representing many classes of singular integral operators, these methods are not equally effective in dealing with Fourier Integral Operators. In this paper, we show that the shea...

This paper proposes an image interpolation algorithm exploiting sparse representation for natural images. It involves three main steps: (a) obtaining an initial estimate of the high resolution image using linear methods like FIR filtering, (b) promoting sparsity in a selected dictionary through iterative thresholding, and (c) extracting high frequency information from the approximation to refin...

In a recent article, we showed that trigonometric shearlets are able to detect directional step discontinuities along edges of periodic characteristic functions. this paper, extend these results bivariate functions which have jump in higher order derivatives edges. prove suitable upper and lower bounds for the shearlet coefficients, need generalize about localization- orientation-dependent deca...

Astronomical images of galaxies can be modeled as a superposition of pointlike and curvelike structures. Astronomers typically face the problem of extracting those components as accurate as possible. Although this problem seems unsolvable – as there are two unknowns for every datum – suggestive empirical results have been achieved by employing a dictionary consisting of wavelets and curvelets c...