Image registration method and system based on feature guiding GMM and edge image

Abstract

The invention relates to an image registration method and system based on a feature guiding GMM and an edge image. Edge images of two to-be-matched images are calculated, feature point sets of the edge images are extracted, according to feature description vectors, a membership degree of a GMM model is set, a model corresponding to geometric transformation between to-be-matched images is established, and a model parameter is calculated by using an optimization method; a posterior probability of a matching point of a feature point in another feature point set of a feature point in the feature point set is calculated again and whether the feature points are matched points mutually is determined according to a threshold value. According to the invention, modeling is carried out for an affine transformation phenomenon between to-be-matched images; and compared with the previous optimization method, the provided method has better robustness and higher accuracy; and the performances are stable under the circumstance that the data degradation is severe.

Description

technical field [0001] The invention relates to the technical field of image feature matching, in particular, the invention relates to an image registration technical solution based on a feature-guided Gaussian mixture model (GMM) and an edge image. Background technique [0002] The basic goal of image matching is to match the same parts of two images of the same scene obtained by different sensors at different times and perspectives. In many matching scenarios, due to factors such as the image sensor and imaging technology used, the environmental conditions of image acquisition, and the change of the scene itself over time, the images used for matching often have problems such as serious degradation and changes in details. Consistent feature reduction is a challenging problem for the registration of such images. In this invention, we focus on the problem of registration of more degraded images, where two or more images of similar scenes with different states are required, ...

AI Technical Summary

Problems solved by technology

In many matching scenarios, due to factors such as the image sensor and imaging technology used, the environmental conditions of image acquisition, and the change of the scene itself over time, the images used for matching often have problems such as serious degradation and changes in details. Consistent feature reduction is a very challenging problem for the registration of such images

For images with serious image quality degradation, it is difficult to extract reliable regional features

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