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Performance evaluation for image fusion technique in medical images using spatial and transform method

机译:使用空间和变换方法的医学图像图像融合技术性能评估

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摘要

Image fusion is the process of combining two or more different images into a new single image, it reduce uncertainty and redundancy in the output while maximizing relevant information from two or more images of a scene into a single composite image that is more informative. This paper presents two basic fusion domains, namely spatial domain and transform domain. Principal component analysis (PCA) which is spatial domain technique and discrete cosine transform (DCT), discrete wavelet transform (DWT), stationary wavelet transform (SWT), non-sub sampled contourlet transform (NSCT), and complex contourlet transform (CCT) which are transform domain techniques. Performance metrics are implemented to evaluate and validate the performance of image fusion technique. Experimental results suggest that the image fusion method based on complex contourlet transform (CCT) is better than other methods.
机译:图像融合是将两个或多个不同的图像组合成一个新的单个图像的过程,它减少了输出中的不确定性和冗余,同时将来自场景的两个或多个图像的相关信息最大化为一个信息量更大的单个合成图像。本文提出了两个基本的融合域,即空间域和变换域。主成分分析(PCA)是空间域技术和离散余弦变换(DCT),离散小波变换(DWT),固定小波变换(SWT),非子采样轮廓波变换(NSCT)和复杂轮廓波变换(CCT)这是变换域技术。执行性能指标以评估和验证图像融合技术的性能。实验结果表明,基于复杂轮廓波变换(CCT)的图像融合方法优于其他方法。

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