基于多尺度SIFT的遥感图像配准

Ibrahim El Rube', Maha A. Sharks, Ashor R. Salem
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引用次数: 15

摘要

图像配准是计算机视觉、遥感和医学图像处理等许多应用领域的重要步骤。图像配准是根据估计的两幅或多幅图像之间的变换对其进行对齐。本文提出了一种结合多尺度小波变换和尺度不变特征变换(SIFT)的图像配准算法。首先,利用小波变换(Wavelet Transform, WT)将图像分解成多个尺度,然后将一定水平的低频(近似)图像输入到SIFT算法中。该算法提高了图像间对应关系的计算速度。不同遥感影像的实验结果验证了该算法的准确性。
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Image registration based on multi-scale SIFT for remote sensing images
Image registration is the step in many application areas such as computer vision, remote sensing and medical image processing. Image registration is achieved by aligning two or more images according to the estimated transformation between them. In this paper, we present an image registration algorithm, which combines the multi-scale wavelet transform with Scale Invariant Feature Transform (SIFT). First, images are decomposed into multiple scales using Wavelet Transform (WT), then the low frequency (approximation) image at certain level is input to SIFT algorithm. The proposed algorithm speeds up the calculation of the correspondences between images. Experimental results with different remote sensing images illustrate the accuracy of proposed algorithm.
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