| 肖明霞,鲁昌华,韦海成,蒋薇薇.基于航拍图像去雾增强的秸秆焚烧监测技术研究[J].电子测量与仪器学报,2017,31(4):543-548 |
| 基于航拍图像去雾增强的秸秆焚烧监测技术研究 |
| Study on monitoring technology of straw burning based on UAV aerial image dehazing enhancement algorithm |
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| DOI：10.13382/j.jemi.2017.04.008 |
| 中文关键词: 无人机航拍 暗通道先验 去雾算法 |
| 英文关键词:UAV aerial image dark channel prior dehazing algorithm |
| 基金项目:宁夏回族自治区青年教学改革研究项目（NXJG2016055）、国家自然科学基金(61461001，61463001)、国家重大仪器开发专项（２０１３ＹＱ220643）资助项目 |
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| Author | Institution |
| Xiao Mingxia | 1. School of Computer and Information, Hefei University of Technology, Hefei 230009, China;
2. School of Electrical and Information Engineering, Beifang University for Nationalities, Yinchuan 750021, China |
| Lu Changhua | School of Computer and Information, Hefei University of Technology, Hefei 230009, China |
| Wei Haicheng | School of Electrical and Information Engineering, Beifang University for Nationalities, Yinchuan 750021, China |
| Jiang Weiwei | School of Computer and Information, Hefei University of Technology, Hefei 230009, China |
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| 中文摘要: |
| 秸秆焚烧会造成严重的大气污染，航拍检测秸秆焚烧能够实现实时监测，具有便捷、实时的特点。但秸秆焚烧点航拍监测图像受天气中悬浮粒子影响，画质退化严重。针对该问题，提出来一种新的图像增强算法。算法在传统的暗通道先验算法基础上，对图像的直方图进行统计并采用自适应系数的去雾增强算法修正，并通过对比度增强最终提高航拍图像的质量。主客观实验结果表明，该算法在白天浓雾环境以及夜晚的低亮度环境下有较好的画质增强效果和较高的实用价值。 |
| 英文摘要: |
| The straw burning will cause serious atmospheric pollution. Aerial detection can achieve real time monitoring of straw incineration conveniently. But the aerial monitoring image of straw burning point can be affected by suspended particles, which will cause the quality of the image degradation seriously. To solve this problem, a new image enhancement algorithm is proposed in this paper. Based on the traditional dark channel prior algorithm, the histogram of the image is statistically analyzed. The adaptive coefficients are used to modify the image enhancement algorithm. And the contrast enhancement is used to improve the quality of aerial image ultimately. The experimental results show that the algorithm has better image quality enhancement effect and higher practical value both in the fog environment day time and low brightness environment night time. |
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