基于天空区域识别暗通道算法的红外图像去雾
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2021年度河南省重点研发与推广专项科技攻关项目(No.212102210385);鹤壁职业技术学院校本科技类重点项目(No.2020-KJZD-002)资助。


Infrared image dehazing based on sky region recognition of DCP
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    摘要:

    为了提高红外图像去雾的效果,提出天空区域识别暗通道算法。首先通过双阈值把有雾图像划分为天空区域、非天空区域、交叉区域;接着天空区域、非天空区域、交叉区域的大气光值、透射率采用不同的方法计算,避免了暗通道算法的局限性;最后给出了算法流程。实验结果表明,本文算法对含有天气区域有雾图像的去雾结果清晰,平均梯度、综合评价相比其他算法较好,本文算法对天空区域与非天空区域有比较复杂的交叉区域的红外图像去雾后的平均梯度值相比暗通道算法提高了28.02,综合评价值提高了19.88。

    Abstract:

    In order to improve the effect of infrared image dehazing,sky region recognition of DCP is proposed.Firstly,image hazing was divided into sky region,non sky region and cross region by double thresholds.Secondly,the atmospheric light value and transmittance of sky region,non sky region and cross region were calculated using different methods to avoid the limitations of dark channel prior.Finally,the process was given.Experimental results show that sky region recognition and dark channel prior algorithm is clear for image dehazing in the sky area,and the average gradient and comprehensive evaluation are better than other algorithms.The average gradient of the infrared image with complex cross areas between the sky area and non sky area is 28.02% higher than dark channel prior algorithm,and the comprehensive evaluation value is 19.88% higher than dark channel prior algorithm.

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邵明省.基于天空区域识别暗通道算法的红外图像去雾[J].激光与红外,2021,51(7):956~961
SHAO Ming-sheng. Infrared image dehazing based on sky region recognition of DCP[J]. LASER & INFRARED,2021,51(7):956~961

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  • 最后修改日期:2020-10-23
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  • 在线发布日期: 2021-07-22