期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2004
卷号：XXXV Part B3
页码：698-703
出版社：Copernicus Publications
摘要：In many image-processing applications it is necessary to register multiple images of the same scene acquired by different sensors, or images taken by the same sensor but at different times. Mathematical modeling techniques are used to correct the geometric errors like translation, scaling and rotation of the input image to that of the reference image, so that these images can be used in various applications like change detection, image fusion etc. In the conventional methods, these errors are corrected by taking control points over the image and these points are used to establish the mathematical model. The objective of this paper is to implement and evaluate a set of automatic registration algorithms to correct the geometric errors of the input image with respect to the reference image, by increasing the accuracy level of the registration and reducing the RMS error to less than a pixel. Various algorithms such as Wavelet transformation method, Fast Fourier transformation method, Morphological Pyramid approach and Genetic Algorithms are developed and compared. These algorithms are capable of considering the transformation model to sub-pixel accuracy. The benefits of these methods are accuracy, stability of estimation, automated solution and the low computational cost
