Image splicing method based on SIFT feature point matching

A feature point matching and image stitching technology, applied in the field of image processing, can solve the problems of unclear fusion images and low efficiency of image stitching technology, and achieve the effects of eliminating chromatic aberration, improving operating efficiency, and improving efficiency and accuracy
CN107154017AInactive Publication Date: 2017-09-12重庆信科设计有限公司
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
重庆信科设计有限公司
Publication Date
2017-09-12
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention discloses an image splicing method based on SIFT feature point matching. The method comprises steps of performing dimensionality reduction of feature descriptors by using a bidirectional 2DPCA method, so as to improve the efficiency and precision of matching; performing crude purification of feature points by the geometrical consistency between the matching feature point pairs, so as to improve the operation efficiency of the random sampling consistency method; performing image fusion by adopting Contourlet transform and eliminating the chromatic aberration of the fusion image, so as to achieve high quality splicing effect of two images. The image splicing method based on SIFT feature point matching solves the problems that the conventional image splicing method is low in matching precision and efficiency, and the fusion image is not clear.
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Description

technical field

[0001] The invention relates to an image splicing method, in particular to an image splicing method based on SIFT feature point matching, and belongs to the technical field of image processing. Background technique

[0002] Image stitching is to fuse multiple images with a certain overlap to synthesize a high-resolution image with a wide field of view and no obvious stitching gaps. At present, image stitching technology has gradually become a research hotspot, and it is widely used in computer image processing, seabed exploration, medical image, virtual reality, remote sensing image processing and other fields.

[0003] The methods of image stitching can be basically divided into the following two types: methods based on gray information and methods based on features. The method based on grayscale information calculates the similarity of two images by using the pixel values ​​of the image to be stitched, so as to determine the overlapping area of ​​stitching...

Claims

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