Statistical correlation based quick mutual information image matching method

Abstract

The invention discloses a statistical correlation based quick mutual information image matching method. The statistical correlation based quick mutual information image matching method comprises the following steps: calculating and storing a histogram and entropy of each of a measured drawing and a first position datum subgraph as well as a joint-histogram, joint entropy and mutual information of the measured drawing and the first position datum subgraph through a traditional method; in a traversal searching process, calculating the histogram and the entropy of the current position datum subgraph as well as the joint entropy of the current position datum subgraph and the measured drawing through a difference method by utilizing dependency of adjacent datum subgraphes and taking the histogram and the entropy of the previous position datum subgraph as well as the joint entropy of the previous position datum subgraph and the measured drawing as datum, and calculating mutual information; and finally, finding the position with a maximal mutual information value among all searched positions as a final matching positioning result. Except from the first position datum subgraph, histograms, entropy and joint entropy of other position subgraphes are sequentially obtained through the difference method, so that mutual information matching speed is increased while matching precision is guaranteed. Besides, the statistical correlation based quick mutual information image matching method can be combined with an existing method, so that the matching speed is increased through various ways.

Description

technical field [0001] The invention belongs to the technical fields of image matching and image positioning, and in particular relates to a fast mutual information image matching method based on statistical correlation. Background technique [0002] Image matching technology is a new technology developed on the basis of aerospace technology, satellite application technology, sensor technology, computer technology, image processing and pattern recognition. It has important application value in military fields such as terminal guidance, image target search and tracking. At present, matching technology is widely used in industrial control, medical image processing, remote sensing image processing, cartography, target recognition and other fields. In applications such as vision-based aircraft navigation and guidance, remote sensing satellite disaster monitoring and environmental monitoring, and medical image analysis, it is often necessary to match heterogeneous images acquire...

AI Technical Summary

Problems solved by technology

Among the above methods, the grayscale compression method and the feature extraction method will lose part of the grayscale information of the image and affect the matching accuracy, while the particle swarm optimization method is easy to fall into local extremum and affect the matching accuracy. The Powell method has higher requirements for the initial point. The selection of the initial point will directly affect the final search for the optimal value

In short, most of the traditional fast mutual information matching algorithms speed up the matching speed by reducing the grayscale or reducing the number of pixels participating in the mutual information measurement calculation, which will affect the matching accuracy to a certain extent.

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