基于简单线性迭代聚类优化的无人机图像去雾算法及其在风电场中的应用
摘要：针对电力巡检过程中无人机（unmanned aerial vehicle，UAV）载荷因受雾气颗粒影响而导致UAV图像不清晰的问题，提出一种基于简单线性迭代聚类（simple linear iterative clustering，SLIC）优化的UAV图像去雾算法。通过雾天成像物理模型、暗通道先验定律、同质滤波与SLIC算法，改善电力巡检图像中白色区域及不均匀光照的影响，提升UAV图像去雾处理的效率，并对大气光强度参数进行自适应计算，以防止去雾过程中复原失真。实验结果表明提出的算法可有效恢复电力巡检图像的原始细节，并通过主观视觉评估及融合多种客观评价指标的对比，说明该算法相对于传统算法的优越性。
Abstract:In order to solve the problem that the unmanned aerial vehicle (UAV) image is not clear due to the influence of fog particles, a UAV image dehazing algorithm based on simple linear iterative clustering (SLIC) optimization was proposed. Through the physical model of fog imaging, the prior law of dark channel, homogeneous filtering and SLIC algorithm, the influence of white area and uneven light in power inspection image was improved, the efficiency of UAV image dehazing was improved, and the adaptive calculation of atmospheric light intensity parameters was carried out to prevent the distortion in the dehazing process. The experimental results show that the algorithm can effectively restore the original details of the power inspection image. Through the comparison of subjective visual evaluation and fusion of a variety of objective evaluation indexes, it shows the superiority of the algorithm compared with the traditional algorithms.
标题：基于简单线性迭代聚类优化的无人机图像去雾算法及其在风电场中的应用
title:Unmanned Aerial Vehicle Image Dehazing Algorithm Based on Simple Linear Iterative Clustering Optimization and Its Application in Wind Farm
作者：刘厦, 孙哲, 仇梓峰, 胡炎
authors:Sha LIU, Zhe SUN, Zifeng QIU, Yan HU
关键词：风电场,电力巡检,图像去雾,同质滤波,简单线性迭代聚类(SLIC),
keywords:wind farm,power inspection,image dehazing,homogeneous filtering,simple linear iterative clustering (SLIC),
发表日期：2020-12-31
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