Serious barrel distortion image correction method based on nonlinearity inverse mapping principle

Abstract

The invention provides a serious barrel distortion image correction method based on a nonlinearity inverse mapping principle. The correction method includes the steps: firstly, confirming the basic correction relation of a barrel distortion image; further, solving the barrel distortion correction relation based on the nonlinearity inverse mapping principle; calculating the polar radius, corresponding to the polar radius in the barrel distortion image, of each pixel in a restore image point-by-point; then mapping the barrel distortion image and the restore image from a polar coordinate system to a standard coordinate system; and giving pixel grey values of the corresponding position of the barrel distortion image to the restore image. Therefore, correction is accomplished. By means of the serious barrel distortion image correction method based on the nonlinearity inverse mapping principle, all cavities in a serious barrel distortion correction image are eliminated completely, the restored grey values at the cavity position can reflect the grey information of an original image correctly, therefore, the information of the restore image is integral and correct, and image quality is improved further.

Description

technical field [0001] The invention relates to a distortion correction method for completely eliminating corrected holes in barrel-shaped distorted images, in particular to a distortion correction method for completely eliminating corrected holes in severely barrel-shaped distorted images. Background technique [0002] In many computer vision fields such as aerospace and aerial photography, medical electronic endoscope, robot and vehicle navigation, visual monitoring and virtual scene technology, it is often necessary to obtain images with a wider range of viewing angles. The full-frame fisheye lens has a larger viewing angle range than a wide-angle lens, can accommodate more scenes, and can adapt to shooting in a small space. Although it inevitably introduces serious barrel distortion while obtaining a super-large field of view image, the image After distortion correction, rich and accurate data information can be extracted, so it has a high application value in various in...

AI Technical Summary

Problems solved by technology

The current common hole filling methods mentioned above cannot completely and correctly fill all the holes

For example: the median filtering and mean filtering methods can eliminate the holes in the middle area of ​​the restored image, but the more holes in the edge area cannot be completely eliminated, and the image becomes blurred at the same time; the hole filling method based on the neighborhood will cause the filled area to be blurred, even wrong information

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