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首页> 外文期刊>Pattern recognition and image analysis: advances in mathematical theory and applications in the USSR >Color Medical Imaging Fusion Based on Principle Component Analysis and F-Transform
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Color Medical Imaging Fusion Based on Principle Component Analysis and F-Transform

机译:基于主成分分析和F变换的彩色医学图像融合

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摘要

In last years, various medical image fusion algorithms have been proposed to fuse medical image. But, most of them focus on fusing grayscale images. This paper proposes a qualified algorithm for the fusion of multimodal color medical images. The technique of F-transforms has mainly been employed as a fusion technique for images obtained from equal or different modalities. The restriction of fused color mixing RGB, substitution method is resolved by incorporating F-transform and color mixing RGB. The proposed method significantly outperforms the traditional methods in terms of both visual quality and objective evaluation, with improved contrast and overall intensity. The proposed method provides better visual information than the gray ones and more adaptable to human vision. Additional, PCA is functional on the two-level decomposition to maximize the spatial resolution. Experimental evaluation demonstrates that the proposed algorithm qualitatively outperforms many existing state-of-the-art multimodal image fusion algorithms.
机译:在去年,已经提出了各种医学图像融合算法融合了医学图像。但是,他们中的大多数都专注于融合灰度图像。本文提出了一种融合多模式彩色医学图像的合格算法。 F变换技术主要是用作从等于或不同模式获得的图像的融合技术。通过掺入F变换和颜色混合RGB来解决熔融颜色混合RGB的限制,替代方法。该方法在视觉质量和客观评估方面显着优于传统方法,具有改善的对比度和总体强度。所提出的方法提供比灰色灰色更好的视觉信息,更适应人类视力。另外,PCA在两级分解上是功能,以最大化空间分辨率。实验评估表明,所提出的算法定性地优于现有的最先进的多峰图像融合算法。

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