Bi-ComForWaRD: BIVARIATE COMPLEX FOURIER-WAVELET REGULARIZED DECONVOLUTION FOR MEDICAL IMAGING

作     者：Rao, M. Venu Gopala Vathsal, S. 

作者机构：Narasaraopeta Engn Coll Guntur Dt AP India JBIET Hyderabad Andhra Pradesh India 

出 版 物：《INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE AND APPLICATIONS》 (国际计算智能及应用杂志)

年 卷 期：2009年第8卷第2期

页      面：85-95页

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Computed tomography complex wavelets medical imaging bivariate shrinkage function deconvolution denoising 

摘      要：In this paper, we propose a new hybrid Bivariate Complex Fourier Wavelet Regularized Deconvolution (Bi-ComForWaRD) that is an extension to the ComForWaRD algorithm, for medical imaging. This new algorithm is a two-step process, a global blur compensation using generalized Wiener filter and followed by a denoising algorithm using local adaptive Bivariate shrinkage function. It is a low-complexity denoising algorithm using the joint statistics of the wavelet coefficients and considers the statistical dependencies between the coefficients. And also, the performance of this system will be demonstrated on both the orthogonal wavelet transform and the dual-tree complex wavelet transform (DT-CWT) and some comparisons with the best available wavelet-based image denoising results will be given in order to illustrate the effectiveness of the system.