Image processing covers a wide range of processing techniques. Image Fusion is one of those technique which plays a vital role with medical images since different imaging methods provide different set of clinical information for diagnosis. Advances in technology provide us with plenty of imaging modalities. Image fusion is essential for a joint analysis of these multimodality images since each of these modalities provide unique and complementary characterization of the underlying anatomy and tissue microstructure. This paper analyzes the image fusion methods based on multiscale transforms and implements using wavelet, contourlet, curvelet, and shearlet transform. The results are compared.

中文翻译：

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基于多尺度变换的像素级图像处理实现分析

图像处理涵盖了广泛的处理技术。图像融合是一种对医学图像起着至关重要作用的技术，因为不同的成像方法为诊断提供了不同的临床信息集。技术的进步为我们提供了大量的成像方式。图像融合对于这些多模态图像的联合分析至关重要，因为这些模态中的每一种都提供了底层解剖结构和组织微观结构的独特和互补表征。本文分析了基于多尺度变换的图像融合方法，并使用小波、轮廓波、曲线波和剪切波变换来实现。结果进行了比较。