Image enhancement and image matching of UAV based on histogram equalization

2021 28th International Conference on Geoinformatics Pub Date : 2021-11-03 DOI:10.1109/ieeeconf54055.2021.9687650

Jingchun Zhou, Wenfei Xi, Dongsheng Li, Hongzhi Huang

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Abstract

High-resolution images can be obtained by using UAV technology, but the quality of UAV images is closely related to external factors when shooting, and the quality of images determines the effect of matching images. The histogram equalization method is a common image enhancement algorithm, and it processes the image gray value of each pixel using the cumulative probability distribution function to obtain an “evenly” distributed histogram, get a clear image, and can improve image recognition. Based on this idea, this paper processes exposed UAV images by using a histogram equalization algorithm. Combined with the SIFT feature point extraction algorithm, it eliminates matching coarse using RANSAC algorithm to obtain high precision homographic matrix, which completes the UAV image matching. In this paper, a group of UAV images was selected for verification. The verification results showed that the extraction of feature points is increased by 16.2% and the information entropy of images is increased by 2.0617. Image enhancement of UAV images can improve the image matching effect.

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基于直方图均衡化的无人机图像增强与图像匹配

利用无人机技术可以获得高分辨率图像，但无人机图像的质量与拍摄时的外部因素密切相关，图像的质量决定了匹配图像的效果。直方图均衡化方法是一种常用的图像增强算法，它利用累积概率分布函数对图像各像素点的灰度值进行处理，得到“均匀”分布的直方图，得到清晰的图像，可以提高图像的识别能力。基于此思想，本文采用直方图均衡化算法对暴露的无人机图像进行处理。结合SIFT特征点提取算法，利用RANSAC算法消除匹配粗糙，获得高精度的同形矩阵，完成无人机图像匹配。本文选取一组无人机图像进行验证。验证结果表明，该方法提取的特征点提高了16.2%，图像信息熵提高了2.0617。对无人机图像进行图像增强，可以提高图像匹配效果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2021 28th International Conference on Geoinformatics

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