Multi-resolution system for artifact removal and edge enhancement in computerized tomography images

Authors:
S. Arivazhagan;S. Deivalakshmi;K. Kannan;B. N. Gajbhiye;C. Muralidhar;Sijo N. Lukose;M. P. Subramanian
Affiliations:
Department of ECE, Mepco Schlenk Engineering College, Mepco Engineering College Post, Sivakasi 626 005, Tamil Nadu, India;Department of ECE, Mepco Schlenk Engineering College, Mepco Engineering College Post, Sivakasi 626 005, Tamil Nadu, India;Department of ECE, Mepco Schlenk Engineering College, Mepco Engineering College Post, Sivakasi 626 005, Tamil Nadu, India;NDED, Defence Research Development Laboratory, Hyderabad 500 058, Andhra Pradesh, India;NDED, Defence Research Development Laboratory, Hyderabad 500 058, Andhra Pradesh, India;NDED, Defence Research Development Laboratory, Hyderabad 500 058, Andhra Pradesh, India;NDED, Defence Research Development Laboratory, Hyderabad 500 058, Andhra Pradesh, India
Venue:
Pattern Recognition Letters
Year:
2007

Citing 9
Cited 1

Fundamentals of digital image processing

Fundamentals of digital image processing
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation

IEEE Transactions on Pattern Analysis and Machine Intelligence
Authenticating Edges Produced by Zero-Crossing Algorithms

IEEE Transactions on Pattern Analysis and Machine Intelligence
Characterization of Signals from Multiscale Edges

IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing

Digital Image Processing
Texture classification using wavelet transform

Pattern Recognition Letters
Fast Boundary Detection: A Generalization and a New Algorithm

IEEE Transactions on Computers
De-noising by soft-thresholding

IEEE Transactions on Information Theory
Image enhancement via adaptive unsharp masking

IEEE Transactions on Image Processing

Software architecture for multi-bed FDK-based reconstruction in X-ray CT scanners

Computer Methods and Programs in Biomedicine

Quantified Score

Hi-index	0.10

Visualization

Abstract

The aim of image enhancement means adopting some technical method, which includes algorithm, to stand out the interested characteristics of the image and to restrain some useless characteristics of the image. The image, which has been improved, can satisfy some special analysis better than the original one. In this paper, we propose a new method for ring artifact removal and edge enhancement for industrial CT images based on the multi-resolution techniques such as, discrete wavelet transform (DWT), stationary wavelet transform (SWT) and dual tree complex wavelet transform (DT-CWT). The performance of the proposed method is compared and analyzed in detail and the promising results and findings are presented.