Homonymous point matching method of heterogenous remote sensing images taking high-order structural characteristics into consideration

Abstract

The invention provides a homonymous point matching method of heterogenous remote sensing images taking high-order structural characteristics into consideration, and belongs to the field of plotting science and technology. The method comprises that data is prepared before heterogenous images are matched; a characteristic point cluster is divided and extracted; candidate matching points of characteristic points are determined; homonymous points are matched taking the high-order structural characteristics into consideration; a result is matched for each layer of pyramid images, and a local network adjustment based on an RFM model is carried out by utilizing a fusion selecting weight iteration method; and the matching result is refined layer by layer till an original image layer, and the homonymous points of the heterogenous remote sensing images can be matched automatically and reliably. According to the invention, a rational function model and a hypergraph image matching model are used in an integrated manner, geometrical constraint characteristics and the higher-order structural characteristics are introduced to layer-by-layer pyramid image matching, the sparsity of the hypergraph model is ensured, and information loss caused by hyperedge sampling is reduced to the minimum; and the matching reliability and success rate of the heterogenous remote sensing images are improved, and the workload of manual homonymous point measurement is reduced effectively.

Description

technical field [0001] The invention belongs to the field of surveying and mapping science and technology, and relates to a method for matching homonymous points of heterogeneous remote sensing images, in particular to a method for matching homonymous points of heterogeneous remote sensing images in consideration of high-order structural features. Background technique [0002] With the rapid development of earth observation technology, various types of sensors have sprung up. They record the changes of the earth's surface with higher time resolution and spatial resolution, and also make the images covering the same area more and more diverse. . The joint target positioning of heterogeneous remote sensing images has become one of the important research directions in the field of photogrammetry and remote sensing. However, whether it is single-point 3D positioning or block adjustment, it is necessary to quickly and accurately find the same name point of the image and measure ...

AI Technical Summary

Problems solved by technology

However, the focus of its research is to integrate the beam block adjustment method based on the RFM model into the same-name point matching process, use the geometric constraints provided by the RFM model, improve the prediction accuracy of the initial point position of the feature points, and provide epipolar line geometric constraints to narrow the matching The search space and the block adjustment based on the RFM model eliminate the wrong matching points, but it is still a single-point matching in essence, and the high-order structural features between the matching points are not introduced in the matching process

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