北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2016, Vol. 39 ›› Issue (6): 33-36,71.doi: 10.13190/j.jbupt.2016.06.006

• 论文 • 上一篇    下一篇

大气散射校正静态实时偏振图像去雾技术

夏璞1,2, 刘学斌1   

  1. 1. 中国科学院西安光学精密机械研究所 中国科学院光谱成像技术重点实验室, 西安 710119;
    2. 中国科学院大学, 北京 100049
  • 收稿日期:2016-03-01 出版日期:2016-12-28 发布日期:2017-01-13
  • 作者简介:夏璞(1989-),男,博士生,E-mail:xiapu16@163.com;刘学斌(1965-),男,研究员.
  • 基金资助:
    国家高技术研究发展计划(863计划)项目(20137031071B);国家自然科学基金项目(11327303)

Real-Time Static Polarimetric Image Dehazing Technique Based on Atmospheric Scattering Correction

XIA Pu1,2, LIU Xue-bin1   

  1. 1. Key Laboratory of Spectral Imaging Technology, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an 710119, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2016-03-01 Online:2016-12-28 Published:2017-01-13

摘要: 为了在雾霾天气下实现静态实时图像去雾,研究了大气衰减模型,分析了大气溶胶对成像的影响和大气散的射校正方法,提出了偏振去雾方法的技术原理.利用斯托克斯参数和穆勒矩阵实现原始数据的静态获取,基于偏振测量结果实现天空区域的实时提取,通过提取结果定性和定量分析,找到了偏振角范围和大气散射光强度阈值的规律性,实现了静态实时偏振去雾.静态实时偏振去雾方法将原始数据由不确定的偏振图像改变为固定的偏振图像,克服了对手动操作和主观评价的依赖,简化了去雾流程,解决了复杂的全局参数估计问题,提高了图像复原的准确度.所提出的静态实时偏振去雾方法为雾霾天气下高分辨、高稳定性和高实时性成像提供了新的理论和技术手段.

关键词: 图像去雾, 大气散射, 大气溶胶, 偏振分析, 图像复原

Abstract: In order to realize real-time static image recovery under hazy weather, a new theory of polarimetric dehazing was presented based on study of the atmospheric scattering model, analyzation on the effects of aerosols and the method of atmospheric scattering correction. The polarimetric information is obtained statically from the original images by Stokes equation and the Muller matrix. The sky region is extracted in real time based on the polarimetric measurement of the hole image. The influence of the range of polarization orientation angle and the threshold of air light intensity are analyzed based on the extraction result. The real time static polarimetric image dehazing method can be realized with fixed linear polarimetric images. No manual operation or subjective evaluation is needed which greatly simplifies the dehazing process. The accuracy of image recovery is increased by solving the problem of the estimation of the global parameters. The real time static polarimetric dehazing method provides a new theoretical and technical way for high-resolution, high stability and real-time image recovery under hazy weather.

Key words: image defogging, atmospheric scattering, aerosol, polarization analysis, image restoration

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