We compared a Bayesian reconstruction method with conventional filtered back projection (FBP) method in positron emission tomography (PET). In the medical scene, PET scanning plays an important role for functional diagnosis such like measuring the cerebral glucose metabolisms. Tomographic image is reconstructed from the observed data, which is the recieved signals from administrated-radioactive...

An image or volume of interest in positron emission tomography (PET) is reconstructed from gamma rays emitted a radioactive tracer, which are then captured and used to estimate the tracer’s location. The by estimating pixel voxel values on grid determined scanner. Such an approach usually associated with limited resolution reconstruction, high computational complexity due slow convergence noisy...

we study the problem of reconstructing binary images from four projections data in a fuzzy environment. given the uncertainly projections,w e want to find a binary image that respects as best as possible these projections. we provide an iterative algorithm based on fuzzy integer programming and linear membership functions.

In this paper, a new method for gray-scale image and color zooming algorithm based on their local information is offered. In the proposed method, the unknown values of the new pixels on the image are computed by Moving Least Square (MLS) approximation based on both the quadratic spline and Gaussian-type weight functions. The numerical results showed that this method is more preferable to biline...

We develop a hyperparameter inference method for image reconstruction from Radon transform which often appears in the computed tomography, in the manner of Bayesian inference. Hyperparameters are often introduced in Bayesian inference to control the strength ratio between prior information and the fidelity to the observation. Since the quality of the reconstructed image is controlled by the est...

An image can be reconstructed from the finite set of its orthogonal moments. Since geometric and complex moment kernels do not satisfy orthogonality criterion, direct image reconstruction using them is deemed to be difficult. In this paper, we propose a technique to reconstruct an image from either geometric moments (GMs) or complex moments (CMs). We utilize a relationship between GMs and Stirl...

This paper presents a method for removing focal blur in images using fusion algorithm. Different focal images can be combined to give a single fused image with all focused information. Pattern selective image fusion provides a mechanism for combining multiple images through identifying salient features in the source images and combining those features in to a single fused image. However one of ...

We present an algorithm for analyzing a single calibrated image of a ball and for reconstructing its instantaneous motion (3D velocity and spin) by exploiting motion blur. We use several state-of-the-art image processing techniques for extracting information from the space-variant blurred image, then robustly integrate such information in a geometrical model of the 3D motion. We initially handl...