Model based image reconstruction in Diffuse Optical Tomography relies on both the numerical accuracy of the forward model as well as the computational speed and efficiency of the inverse model. Most model based image reconstruction algorithms rely on Newton type inversion methods, whereby the inverse of a large Jacobian is approximated. In this work we present an efficient Jacobian reduction me...

We describe a closed-form technique for mapping the output of a trained backpropagation network int.o input activity space. The mapping is an inverse mapping in the sense that, when the image of the mapping in input activity space is propagat.ed forward through the normal network dynamics, it reproduces the output used to generate that image. When more than one such inverse mappings exist, our ...

In magnetic resonance imaging, complex-valued measurements are acquired in time corresponding to spatial frequency measurements in space generally placed on a Cartesian rectangular grid. These complex-valued measurements are transformed into a measured complex-valued image by an image reconstruction method. The most common image reconstruction method is the inverse Fourier transform. It is know...

Inverse Synthetic Aperture Radar (ISAR) is a powerful radar processing technique which is capable of two and three dimensional high resolution image generation of the target. ISAR image is often regarded as an adequate and sufficient measure to discriminate between various targets like missiles, military aircraft and civilian aircrafts. However, if the target has complicated motion such as pitc...

Image interpolation is a common problem in imaging applications. However, most interpolation algorithms in existence suffer visually the effects of blurred edges and jagged artifacts in the image to some extent. This paper presents an adaptive feature preserving bidirectional flow process, where an inverse diffusion is performed to sharpen edges along the normal directions to the isophote lines...

Image enhancement is important given that it can be used to highlight the area of interest in images. This article designs four filters via special function for realizing image enhancement. Firstly, a filter based on exponential designed. When value progression even, edge feature extracted. odd, sharp contrast obtained. Secondly, built using hyperbolic cosine and its inverse function, where pri...

In a continuous setting, diffeomorphisms generated by stationary velocity fields (SVF) are invertible transformations with differentiable inverses. However, due to the numerical integration of the velocity field, inverse consistency is not achieved in practice. In SVF based image registration, inverse consistency is therefore often enforced through a penalty term. Existing penalty terms penaliz...

We propose a smooth formulation of multiple-point statistics that enables us to solve inverse problems using gradient-based optimization techniques. We introduce a differentiable function that quantifies the mismatch between multiple-point statistics of a training image and of a given model. We show that, by minimizing this function, any continuous image can be gradually transformed into an ima...

The contemporary information technologies and Internet impose high requirements on the image compression efficiency. Great number of methods for information redundancy reduction had already been developed, which are based on the image processing in the spatial or spectrum domain. Other methods for image compression use some kinds of neural networks. In spite of their potentialities, the methods...

It is well-known that Gaussian filter is the most important model in image denoising. However, the inverse of the Gaussian model for image sharpening is seriously ill-posed. In this paper, we propose several variations of the Gaussian model, which are derived from the varied diffusion equations. Explicit forms for these models (filters) are given in the Fourier space, which facilitate the usage...