Sparse and dense characteristic matching combined image registration method

A dense feature, image registration technology, applied in the field of image processing, can solve problems such as unsatisfactory results

Active Publication Date: 2016-03-23
CHINA UNIV OF GEOSCIENCES (WUHAN)
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Problems solved by technology

They have achieved great success in matching rigid scenes (e.g. in the field of image stitching) and mildly non-rigid scenes (e.g. in the field of medical imaging) Unable to achieve satisfactory results

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  • Sparse and dense characteristic matching combined image registration method
  • Sparse and dense characteristic matching combined image registration method
  • Sparse and dense characteristic matching combined image registration method

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Embodiment Construction

[0051] The present invention will be further described below in conjunction with embodiment.

[0052] The invention provides an image registration method combining sparse and dense feature matching, comprising the following steps:

[0053] (1) Establish a sparse feature matching energy function based on local linear constraints:

[0054] (1-1) Using the feature detection method to infer the hypothetical matching set of the two images to be registered x n with y n Two-bit column vectors representing the spatial positions of the feature points in the two images to be registered respectively; the hypothetical matching set S includes wrong matching and correct matching, wherein the correct matching is determined according to the geometric transformation Z between the two images with matching , that is, if (x n ,y n ) is a correct match, then y n =Z(x n ) is a correct match;

[0055] (1-2) The initial position plus a displacement function v will define a transformation Z: ...

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Abstract

The invention provides a sparse and dense characteristic matching combined image registration method. According to the method, sparse characteristic matching is combined with dense characteristic matching to obtain a new mathematic model which includes two variables, nonrigid geometric transformation and disperse displacement flow field, wherein the nonrigid geometric transformation is applicable to sparse matching flows, and adjusted through introducing local linear constraint to be well posed; and the disperse displacement flow field is applicable to dense matching flows, a model similar to SIFT flows is used and meanwhile a belief propagation algorithm is adopted for optimized solution, and accurate pixel comparison matching can be obtained for a remote sensing image including nonrigid movements.

Description

technical field [0001] The invention relates to an image registration method combining sparse and dense feature matching, and belongs to the technical field of image processing. Background technique [0002] Image registration is a fundamental and challenging problem in the field of remote sensing and a prerequisite in many wide-ranging applications including terrain reconstruction, environmental monitoring, change detection, image mosaicing, image fusion, and map updating, etc. [0003] Image registration aims to establish the correspondence between pixels between two images of the same scene acquired at different times and from different perspectives or by different detectors. Registration problems can be classified as rigid or nonrigid, depending on the application and data format. Rigid registration (involving only a small number of parameters) is relatively easy and has been extensively studied. In contrast, non-rigid registration is more difficult, because the underl...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
CPCG06T2207/10032
Inventor 陈珺罗林波刘超王勇罗大鹏
Owner CHINA UNIV OF GEOSCIENCES (WUHAN)
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