|Table of Contents|

A Medical Image Fusion Algorithm Based on Contourlet Transform and T Mixture Models(PDF)

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2017年01期
Page:
27-
Research Field:
·数学与计算机科学·
Publishing date:

Info

Title:
A Medical Image Fusion Algorithm Based on Contourlet Transform and T Mixture Models
Author(s):
Xu Chunyan; Song Yuqing; Liu Zhe; Bao Xiang
School of Computer Science and Communication Engineering,Jiangsu University,Zhenjiang 212013,China
Keywords:
T distribution mixture models; Contourlet transform; image fusion; GIHS
PACS:
TP391
DOI:
10.3969/j.issn.1001-4616.2017.01.005
Abstract:
Medical image fusion has become a hot research in the field of medical image processing,among which the most classical method called Gaussian mixture models with Expectation Maximum(EM)fusion,the most classical method may lose the local detail. This paper presents a fusion algorithm which is based on Contourlet transform and T mixture models. Firstly,the RGB color space of source images are converted to the GIHS space through GIHS(Generalized Intensity-Hue-Saturation)transform. Secondly,with the Contourlet transform,the intensity component are decomposed into multi-resolution representations,and then the maximum absolute value of coefficient is applied to fuse the high frequency,EM algorithm is used to estimate the parameters of T mixture models. Lastly,the new intensity is obtained by inverse Contourlet,combining hue and saturation to get final result. Experimental results indicate that the proposed algorithm can obtain the results with more functional,spatial information and obtain a better evaluation than other mainstream algorithms.

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