An automatic geometric registration method for multi-source high spatial resolution images

Abstract

An automatic geometric registration method for multi-source high spatial resolution images comprises the following steps: (1) resampling an image to be registered by using a reference image; (2), dividing the processed image to be registered into grids; (3) calculating mutual information quantity between the image to be registered and the zero matrix image in each grid, wherein the region corresponding to the minimum mutual information quantity is taken as the feature matching region in the image to be registered; (4) traversing a reference image by using a feature matching area, calculating the normalized mutual information amount between the feature matching area in each grid and the reference image, and taking the area corresponding to the maximum value of the normalized mutual information amount as the reference image matching area; (5), extracting the center point coordinates of the feature matching area and the reference image matching area, and calculating the final conversion parameters; (6) that image to be register using the final conversion parameter to obtain the result of image registration. The homonymous points are evenly distributed, and the registration accuracy ishigh and the speed is fast.

Description

technical field [0001] The invention relates to the technical field of surveying and mapping geographic information, in particular to an automatic geometric registration method of multi-source high spatial resolution images. Background technique [0002] With the development of remote sensing technology, remote sensing data with different temporal, spatial and spectral resolutions are widely used in various industries, providing an important data source for my country's urban planning, urban construction, urban management and ecological civilization. Geometric registration of different data is the premise and key step to realize the comprehensive application of multi-source remote sensing images. Currently, remote sensing image registration methods mainly include manual registration and automatic registration. [0003] Manual registration is to import the image to be registered and the reference image in professional software, find the same name points between the images ba...

AI Technical Summary

Problems solved by technology

Currently commonly used automatic registration methods include feature-based and grayscale-based automatic registration methods. Feature-based automatic registration methods match images by extracting feature information such as edges, textures, and regions. Common ones include Moravec, Algorithms such as Forstner, Harris, SIFT, etc. This type of method is suitable for images with small matching areas. When the matching area is large, the matching efficiency of this type of method is significantly reduced, and for areas with inconspicuous features, the number of false matches will increase significantly. , the registration accuracy is affected; the grayscale-based automatic registration method mainly relies on the grayscale statistical information on the image. The grayscale statistics of large-area images will also make the matching efficiency of large-area images inefficient.

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