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Image registration method based on SIFT feature and angle relative distance

A technology of relative distance and image registration, applied in the field of image registration and computer image registration based on SIFT features and angular relative distance, it can solve the problem of not being able to completely screen out the correct matching points, and achieve enhanced image registration accuracy, Unique and informative effects

Active Publication Date: 2016-10-12
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

In the past, there have been many studies on the screening of feature points in image registration, such as the RANSAC (Random Sample Consensus) algorithm, the Bayesian model using maximum likelihood estimation, etc., but there are cases where the correct matching points cannot be completely screened out.

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  • Image registration method based on SIFT feature and angle relative distance

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[0065] The hardware environment used for implementation is: Intel(R) Core(TM) 2Duo CPU, E7500, 4GB RAM, 2.94GHz, and the running software environment is: Mat1ab2014a and Win7. We have realized the new algorithm that the present invention proposes with the mixed programming of Matlab language and C++ language. Experiments were conducted using visible light images, near-infrared and visible light images, and remote sensing images, and the image sizes ranged from 384×288 to 3086×2865.

[0066] Step 1. Extract the reference image img ref and the image img to be registered src The scale-invariant feature (SIFT) feature points in: for the reference image img ref and the image img to be registered src The Gaussian kernel function G(x,y,σ) of different scales (σ) is used for continuous filtering and downsampling to form a Gaussian pyramid image, and then the difference of Gaussian (DOG) scale space representation is obtained by subtracting Gaussian images of adjacent scales. Compa...

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Abstract

The invention relates to an image registration method based on SIFT (scale invariant feature transform) feature and angle relative distance. The technical feature is characterized by, to begin with, extracting feature points and feature point descriptors in a reference image and an image to be registered through an SIFT feature point extraction algorithm; then, obtaining a coarse matching result between image feature points through Euclidean distance between the feature points; and with the coarse matching result being input, calculating angle relation of the feature points, and carrying out subtraction to obtain angle difference and screening out correctly-matched feature point pairs. Correctly-matched feature point screening can be carried out by fully utilizing corresponding angle invariant feature of the coarsely-matched feature point pair set, thereby greatly improving correctly-matched feature point pair screening capability, and improving accuracy of image registration.

Description

technical field [0001] The invention belongs to computer image registration methods, and relates to an image registration method based on SIFT (scale invariant feature transform) features and angle relative distances, which is widely used in the fields of image registration and image splicing. Background technique [0002] Image registration is the processing of two or more images taken at different times or from different angles with a common scene, usually only for two images. Image registration is a very meaningful and challenging work, and it is a crucial pre-processing for many applications such as image stitching, and heterogeneous image registration has a wide range of application scenarios in military and medical fields, and its fusion results can be It is used for automatic target camouflage recognition and diagnosis of lesion. [0003] At present, the research on image registration methods is mainly divided into two parts: region-based image registration algorithm...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
Inventor 李晖晖郑平王帅郭雷胡秀华
Owner NORTHWESTERN POLYTECHNICAL UNIV
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