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Review of Multimodal Medical Image Fusion Technology Based on Wavelet Transformation
Author(s): WANG Yuan-jun, JIANG Bo-yu, JIN Zhen-yi, CHANG Wei, ZHANG Ying-zi, Institute of Medical Imaging Engineering, University of Shanghai for Science and Technology
Pages: 4530-
4536+4584
Year: 2013
Issue:
6
Journal: Chinese Journal of Medical Physics
Keyword: image fusion; multimodal; Wavelet Transformation; fusion rule; image quality assessment;
Abstract: Objective: Image Fusion is a hot spot in Image Processing field, which aims to combine different kinds of information from different sensors into an image with high informational density. It is always applied in Medicine, aerial remote sensing,military field, etc. The choice of algorithm has great influence on the fusion result. Methods: Select the mainstream Wavelet Transformation based fusion method as our fusion algorithm. According to the flow chart of Wavelet Transformation, the two main factors that affect the quality of fused image are: transformation base and fusion rule of coefficients in the wavelet domain.This article will conclude fusion methods according to these two parts. Algorithms gathered here are based on two rules: algorithm with better fusion result, higher recitation frequency and popularity. Plus, some of traditional fusion algorithms are concluded briefly here as well. Conclusions: With gathering and analyzing papers of image fusion, we rearrange them according to transformation method and fusion rule. For the transformation method, it has three subcategories: traditional Haar wavelet, improved wavelet and hybrid transformation method. For the fusion rule, three categories as well: pixel, region and hybrid algorithm. Then, several kinds of fused image quality assessments are provided, which will help us evaluate image quality subjectively.
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