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Aviation sequence image position estimating method based on SURF (Speeded Up Robust Features)

A sequence of images, aerial technology, applied in the direction of photo interpretation, etc., can solve the problems of increasing the complexity of the method, large registration errors, etc., to achieve the effect of improving registration accuracy and accuracy

Active Publication Date: 2013-01-09
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

In general, there are large differences (such as scale, rotation, illumination, etc.) between the ground image (real-time image) acquired by the airborne camera and the satellite digital orthophoto image (reference image), and the traditional method based on template matching is Before image registration, it is necessary to predict the heading deviation of the real-time image relative to the reference image based on the planned track, which increases the complexity of the method and the registration error is large

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Embodiment Construction

[0039] Now in conjunction with embodiment, accompanying drawing, the present invention will be further described:

[0040] The embodiment of the present invention mainly includes two core parts: A. SURF feature descriptor extraction of aerial sequence images. B. SURF feature point matching of aerial sequence images. Its implementation steps are as follows:

[0041] The first step is to construct a multi-scale space.

[0042] The second step is fast Hessian matrix detection.

[0043] The third step is SURF feature descriptor extraction.

[0044] The fourth step is to match the feature points based on the Hessian matrix trace.

[0045] The fifth step is local parameter estimation based on RANSAC.

[0046] The specific process is as figure 1 shown.

[0047] 1. Multi-scale space construction

[0048]Adjacent scale difference is related to the size of the Gaussian second-order derivative. For a 9×9 filter, the size of the Gaussian second-order derivative is set to 3, which ...

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Abstract

The invention relates to an aviation sequence image position estimating method based on SURF (Speeded Up Robust Features). The aviation sequence image position estimating method can adapt to rotation of an aviation sequence image, dimension change and noise interference, realize accurate estimation of an airplane. The aviation sequence image position estimating method comprises the following steps of: firstly, structuring SURF dimension space, locating an extreme point by using a quick Hessian matrix, calculating a 64-dimensional SURF describer of the aviation image; then finishing point match on the basis of a Hessian matrix track; at last, eliminating outliers by using a random sample consensus algorithm (RANSAC) method, realizing accurate estimation of a position parameter. The invention aims at a severe working environment of an aircraft and aims to improve precision of visual navigation; compared with a traditional visual navigation method, the method can effectively overcome the shortcoming of nonsensitive to dimension, rotation, light and other factors in the process of position estimation by an unmanned plane, and obviously improve the matching precision of a real-time image and a reference image; and therefore, the method has an important actual meaning for a visual navigation project application of the unmanned plane.

Description

technical field [0001] The invention relates to a method for estimating the position of aerial sequence images based on SURF features. The method can adapt to the rotation, scale transformation and noise interference of aerial sequence images, and realizes accurate estimation of position parameters of real-time images acquired by aircraft on satellite reference images. Background technique [0002] In visual navigation, position parameter estimation is the core of aircraft autonomous navigation, and research on high-precision and robust image matching methods is an important means to improve aircraft position parameter estimation. [0003] The present invention uses Speeded-up robust features (SURF), that is, a new local invariant feature method, to integrate the gradient information of sub-regions, and can effectively solve the problem of geometric transformation and distortion between the real-time image and the reference image. , Affine transformation, viewing angle trans...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C11/04
Inventor 李耀军潘泉赵春晖杨峰梁彦
Owner NORTHWESTERN POLYTECHNICAL UNIV
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