中国计量大学,浙江 杭州 310018
蒋涛(2001— )男,硕士研究生,从事图像处理在环境监测中应用研究。2607229429@qq.com
张光学(1982— ),男,教授,博士,从事能源清洁利用方面的研究。zhangguangxue@cjlu.edu.cn
收稿:2026-01-14,
修回:2026-04-22,
纸质出版:2026-05-20
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蒋涛,张光学,朱莎弘等.基于优化暗通道先验算法的烟雾浓度测量方法研究[J].光学技术,2026,52(03):266-272.
JIANG Tao,ZHANG Guangxue,ZHU Shahong,et al.Smoke concentration measurement using an enhanced dark channel prior algorithm[J].OPTICAL TECHNIQUE,2026,52(03):266-272.
针对传统烟雾浓度监测方法成本高、布点稀疏、难以实现空间连续测量的问题,研究提出一种基于改进暗通道先验的烟雾浓度视觉测量方法。通过优化透射率估计模型,引入自适应暗道补偿机制,建立图像透射率和烟雾浓度的量化关系。实验结果表明,方法可有效地解决传统方法的问题,尤其在实现空间连续测量上有显著优势。方法的测量相对误差仅为7.43%,相关系数达到0.99,测量范围在0.1~1500mg/m³。其均方根误差为43.28mg/m³,优于传统暗通道算法的54.63mg/m³,尤其在高浓度区间表现出更好的稳定性和准确性。研究为烟雾浓度的低成本、可视化监测提供了一种有效技术途径。
To address the issues of high cost
sparse distribution of monitoring points
and difficulty in achieving spatially continuous measurement in traditional smoke concentration monitoring methods
a visual measurement method based on an improved dark channel prior is proposed By optimizing the transmittance estimation model and introducing an adaptive dark channel compensation mechanism
a quantitative relationship between image transmittance and smoke concentration is established.Experimental results demonstrate that the limitations of traditional approaches are effectively resolved by the proposed method
with significant advantages particularly shown in enabling spatially continuous measurement.The method achieves a relative accuracy of 7.43%
a correlation coefficient of 0.99
and a measurement range of 0.1~1500 mg/m³. The root mean square error is measured at 43.28 mg/m³
outperforming the 54.63 mg/m³ value obtained by the traditional dark channel algorithm. Improved stability and accuracy
especially in high-concentration ranges
are demonstrated.An effective technical pathway for low-cost and visual monitoring of smoke concentration is provided by this study.
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