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The existence of numerous imaging modalities makes it possible to present different data present in different modalities together thus forming multimodal images. Component images forming multimodal images should be aligned, or registered so that all
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图像配准：选择图像需要配准的子区域，计算归一化互相关，通过它来确定图像配准的区域，显示配准后的图像。-Image registration: Select the image sub-region need registration, computing normalized cross-correlation, by which to determine the image registration area to show the image after registration.
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基于NCC（归一化互相关）的图像配准算法-NCC (normalized cross-correlation), image registration algorithm
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归一化互相关图像配准
有时一幅图像是另一幅图像的子图像，可以利用归一化互相关通过移动一幅图像来是两幅图像配准。-Normalized cross-correlation image registration Sometimes an image is another image of the sub-image, by moving an image using the normalized cross-correlation to two image registration.
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此程序是在MATLAB下进行图像配准，通过归一化互相关来确定图像配准的区域。-This program is for image registration in MATLAB, by normalized cross-correlation to determine the image registration area.
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图像拼接(image mosaic)技术是将一组相互间重叠部分的图像序列进行空间匹配对准,经重采样合成后形成一幅包含各图像序列信息的宽视角场景的、完整的、高清晰的新图像的技术。图像拼接在摄影测量学、计算机视觉、遥感图像处理、医学图像分析、计算机图形学等领域有着广泛的应用价值。 一般来说,图像拼接的过程由图像获取,图像配准,图像合成三步骤组成,其中图像配准是整个图像拼接的基础。本文研究了两种图像配准算法:基于特征和基于变换域的图像配准算法。 在基于特征的配准算法的基础上,提出一种稳健的基于特征点的
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将归一化互相关应用到图像配准上，使用互相关来判断两幅图像的相似性，相似度越大，说明配准结果越是精确。(The normalized cross-correlation is applied to image registration, and the similarity of two images is judged by cross-correlation. The greater the similarity, the more accurate the registration resu
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