A new algorithm for solving the deconvolution problem is proposed. This algorithm uses the wavelet transform to induce a multiresolution approach to deconvolve a blurred signal/image. The low resolution part of a signal/ image is restored first and then high resolution information is added successively into the estimation process. Two 'different ways to incorporate the image space positivity constraint, namely loosely and strictly, are discussed. In contrast to most restoration algorithms, the positivity constraint is applied directly in the transformed domain. The performance of the algorithm in the presence of noise is also investigated. © lEE, 1997.

Item Type:	Refereed Article
Research Division:	Engineering
Research Group:	Electrical and Electronic Engineering
Research Field:	Control Systems, Robotics and Automation
Objective Division:	Information and Communication Services
Objective Group:	Other Information and Communication Services
Objective Field:	Information and Communication Services not elsewhere classified
UTAS Author:	Liew, AWE (Mr Alan Wee Chung Liew)
UTAS Author:	Law, NF (Miss Ngai Fong Law)
UTAS Author:	Nguyen, DT (Professor Thong Nguyen)
ID Code:	11292
Year Published:	1997
Web of Science® Times Cited:	6
Deposited By:	Electrical Engineering and Computer Science
Deposited On:	1997-08-01
Last Modified:	2011-08-12
Downloads:	0