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计算机系统应用:2018,27(12):257-261
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海天背景图像去雾方法研究
赵越秀, 高俊钗, 李翰山
(西安工业大学 电子信息工程学院, 西安 710021)
Research on Image Dehazing of Sea-Sky Background
ZHAO Yue-Xiu, GAO Jun-Chai, LI Han-Shan
(College of Electronic and Information Engineering, Xi'an Technological University, Xi'an 710021, China)
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投稿时间:2018-05-11    修订日期:2018-06-08
中文摘要: 海天背景图像存在大面积天空区域,且在远距离平视时目标一定出现在海天线附近,现有的去雾算法对天空区域的改善都是弱化天空区域的处理,这样势必会造成海天线附近去雾效果的减弱,不利于后续的目标检测.针对该问题,提出一种基于大气散射模型的图像复原去雾算法.首先,利用海天背景图像的特点,采用边缘检测算子将图像划分为天空和非天空区域,并结合大气光的物理意义,取天空区域最大的值作为大气光的估计值;其次,针对有雾图像对比度很低而雾图像对比度较高这一先验信息设计代价函数,并通过SLIC超像素分割进行分块,通过求解每个小块内该函数的最小值,估计出粗透射率,再用引导滤波对粗透射率进行细化从而消除块效应;最后,利用大气散射模型,代入前两步求得的参数便可以得到恢复的雾图像.实验结果与分析结果表明,本文能对海天背景的图像取得较好的去雾效果.
Abstract:The sea-sky background image has a large area of sky and the target must be near the sea-sky-line when looking from a distance. The existing dehazing algorithms improve the sky area by weakening the processing of the sky area. This will inevitably weaken the dehazing effect near the sea-sky-line and be detrimental to the next target detection. This study proposes the method of atmospheric scattering physical model to dehaze. Firstly, based on the features of the sea-sky background image, the edge detection algorithm is used to divide the image into sky and non-sky regions. Considering the physical meaning of atmospheric light, the maximum value of the sky region is estimated as the value of atmospheric light. Secondly, the cost function is designed based on the prior information that the fog image has low contrast and the fog-free image has high contrast, and dividing the image into blocks by SLIC superpixel segmentation. The rough transmission is estimated by finding the minimum of the function in each block, and then the guided filtering is used to eliminate block effect. Finally, the fog-free image can be obtained by substituting the parameters obtained in the first two steps into atmospheric scattering model. The experimental and analysis results show that this method can achieve better dehazing effect of sea-sky background images.
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基金项目:陕西省科技厅项目(2017GY-037);西安工业大学科研创新团队建设计划项目资助
引用文本:
赵越秀,高俊钗,李翰山.海天背景图像去雾方法研究.计算机系统应用,2018,27(12):257-261
ZHAO Yue-Xiu,GAO Jun-Chai,LI Han-Shan.Research on Image Dehazing of Sea-Sky Background.COMPUTER SYSTEMS APPLICATIONS,2018,27(12):257-261

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