Implementation of generalized cross validation based image denoising in parallel virtual machine environment

Abstract

Paper presents a wavelet based, high performance image denoising scheme implemented in a parallel virtual machine (PVM) environment. Performance of generalized cross validation (GCV) based threshold selection scheme is poorer from CPU time viewpoint when implemented sequentially. In contrast to the traditional parallel approaches, which rely on specialized parallel machines, the present work explores the potential of distributed systems for parallelism. The master/slave model is adopted for control of machines. In this paper the performance of GCV based thresholding algorithm is presented in PVM environment. The proposed algorithm outperforms Donoho and Johnstone's Universal and SureSrink thresholding scheme in most of the test cases. The present investigation validates suitability of GCV thresholding scheme from parallel implementation viewpoint. © 2003 Elsevier Inc. All rights reserved.