A Novel Method for Brain MRI Super-resolution by Wavelet-based POCS and Adaptive Edge Zoom
Journal Title: International Journal on Computer Science and Engineering - Year 2010, Vol 2, Issue 7
Abstract
This paper aims to make the super-resolution of a high-resolution image from a sequence of low-resolution frames containing non-stationary objects. The challenges of making super-resolution image, like unavoidable smoothing effects, introduction of artifacts, computational efficiency in time and computational efficiency in memory requirements, are considered and a novel method is proposed to solve these roblems. The proposed method handles the super-resolution process by using wavelet based projection- nto-convex-set with adaptive edge zoom algorithm. Adaptive edge zoom algorithm address the problem of producing enlarged picture from the given digital image. Wavelet based projection- nto-convex-set method is used to enhance spatial resolution of MRI brain images from a temporal sequence. This method produces more clarity with high peak signal-to-noise ratio.
Authors and Affiliations
N. Hema Rajini , R. Bhavani
Keywords
Related Articles
- EP ID EP102732
- DOI -
- Views 86
- Downloads 0
Context Ontology Construction For Cricket Video
Content based video retrieval systems are not complete in semantic sense. To improve the efficiency and the effectiveness of the retrieval system the content based retrieval systems must be equipped with the semantic bas...
Evolutionary Aspects Of Windows Operating System To Enhance Existing Technology
The evolutionary trends in windows technology tends to hange since from the beginning including kernel, Graphical (GUI), Device drivers, interfaces etc. This paper presents a brief and comprehensive statistical analysis...
A Study of Using Artificial Neural Network in a Non-linear Centrifugal Compressor System
This study adopts the centrifugal compressor system which produces the nitric acid equipment in China Petrochemical Development Corporation’s Plant. The system is non-linear and its manufacturing process is changeable, w...
Collaborative Clustering: An Algorithm for Semi-Supervised Learning
Supervised learning is the process of disposition of a set of consanguine data items which have known labels. The apportion of an unlabeled dataset into a conglomeration of analogous items(clusters) by the optimization o...
PERFORMANCE EVALUATION OF DSR USING A NOVEL APPROACH
In this paper, we propose a novel approach “Routing based on Best First Search Technique (RBFS)” to improve the erformance of Dynamic Source Routing (DSR) for mobile d-hoc wireless networks. The proposed scheme tries t...