Unmanned aerial vehicle multi-spectral image pixel level anisotropy correction method

By employing a pixel-level anisotropy correction method for UAV multispectral images, and utilizing 3D reconstruction and BRDF model fitting, the problem of poor radiometric accuracy in UAV multispectral images with complex land cover and high-resolution imagery is solved, achieving more accurate radiometric error mitigation and image accuracy improvement.

CN119963455BActive Publication Date: 2025-11-04HARBIN INST OF TECH
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Patent Information

Application Number
CN202510028995.0
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-01-08
Publication Date
2025-11-04
Estimated Expiration
2045-01-08

AI Technical Summary

Technical Problem

Existing anisotropy correction methods for UAV multispectral images have limitations in complex land cover and high-resolution image processing, resulting in poor radiometric accuracy.

Method used

A pixel-level anisotropy correction method for UAV multispectral images is adopted. Three-dimensional reconstruction is performed based on UAV multispectral sub-images, geographic location data and attitude data. The three-dimensional coordinates of the pixel region are transformed using digital elevation model and camera parameters. Multi-view data fitting is performed in combination with BRDF model, and downward reflectance is extracted to replace the original reflectance.

Benefits of technology

It achieves more accurate pixel-level ground feature processing, effectively mitigates radiation errors introduced by changes in imaging perspective, and improves image radiation accuracy.

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Abstract

The application discloses a UAV multi-spectral image pixel-level anisotropy correction method, and belongs to the technical field of radiation correction of UAV multi-spectral images. The application aims at the problem that the existing anisotropy correction method has limitations in the processing of complex ground cover and high-resolution images, and causes poor image radiation precision. The method comprises the following steps: three-dimensional reconstruction is carried out based on a UAV multi-spectral sub-image, geographical position data and attitude data to obtain a spliced image, a digital elevation model and optimized camera parameters of the sub-image; pixel region coordinates in the spliced image are converted from a geocentric geodetic coordinate system through a camera coordinate system to an image coordinate system; multi-angle reflectivity is obtained by extracting a projection region of the pixel region in the sub-image; multi-angle data are obtained by calculating an observation imaging angle; a fitting result is obtained by using a general BRDF model to fit the multi-angle data; and the pixel-level anisotropy correction is realized by extracting a downward-looking reflectivity to replace original reflectivity of the spliced image. The application is used for anisotropy correction of UAV multi-spectral images.
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