Fisheye image distortion correction method based on reverse polynomial model

Abstract

The invention discloses a fisheye image distortion correction method based on a reverse polynomial model. The fisheye image distortion correction method adopts a mathematic means that reverse Taylor series fitting is carried out on a polynomial function expression built by a forward model, and a corrected image coordinate which takes a pixel as a unit is converted into an image coordinate which is not corrected and takes a pixel as the unit. Since each corrected image coordinate inevitably corresponds to a certain pixel value in the image which is not corrected through a reverse correction model, a phenomenon that individual pixels of the image are lost after correction can be successfully avoided by reverse correction so as to avoid additional operation, such as interpolation and the like, and meanwhile, a good correction effect and better real-time performance can be obtained. Under a condition that correction precision is almost unchanged, the phenomenon that the pixels of the corrected image are lost is avoided, the real-time performance of the whole correction process is improved, and for an embedded system and a site application occasion, the reverse polynomial model is superior to a traditional forward polynomial correction model.

Description

technical field [0001] The invention relates to the fields of image processing and machine vision, in particular to a fisheye image distortion correction method based on an inverse polynomial model. Background technique [0002] Due to the advantages of large field of view and short focal length, fisheye lenses can be used to expand the field of view of ordinary pinhole cameras. Wide-angle or fisheye cameras with large fields of view are required in many areas of computer vision such as robot navigation, video conferencing, surveillance, and virtual reality. It is widely accepted in most computer vision fields that cameras follow a linear pinhole model. However, the fisheye lens optical system introduces strong optical distortion, which leads to the fact that the assumption of the pinhole model is no longer valid. In order to make full use of the perspective projection information of these severely distorted images, it is necessary to correct the distorted images into idea...

AI Technical Summary

Problems solved by technology

On the whole, due to the introduction of interpolation operation, the real-time performance of the algorithm will be reduced, which will affect the final correction effect

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