遥感影像暗原色统计先验分析
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摘要
遥感影像的成像过程容易受到雾霾的影响,同时雾霾天气日益增多,使得遥感影像去雾工作成为遥感影像数据预处理的重要组成部分。基于暗原色统计先验的暗通道去雾方法已经在自然图像去雾方面得到了广泛应用,而该方法对于遥感影像的适用性还有待评估。以"高分一号"卫星遥感影像为例,讨论了遥感影像的暗原色值特性。结果表明,基于暗原色统计先验的暗通道去雾方法可以应用到遥感影像的雾霾去除工作上。
The imaging process of remote sensing images is easily affected by fog. At the same time,the increase of foggy weather makes the fog removal work of remote sensing images become an important part of remote sensing image data preprocessing. The dark channel fog removal method based on dark color statistical priority is widely used in the defogging of natural images. But for remote sensing images,the applicability of the dark channel fog removal method needs to be evaluated. Taking " GF-1" satellite remote sensing images as an example,the dark color characteristics of remote sensing images are discussed. The result shows that the dark channel fog removal method based on dark color statistic priority can be applied to the fog removal of remote sensing images.
The imaging process of remote sensing images is easily affected by fog. At the same time,the increase of foggy weather makes the fog removal work of remote sensing images become an important part of remote sensing image data preprocessing. The dark channel fog removal method based on dark color statistical priority is widely used in the defogging of natural images. But for remote sensing images,the applicability of the dark channel fog removal method needs to be evaluated. Taking " GF-1" satellite remote sensing images as an example,the dark color characteristics of remote sensing images are discussed. The result shows that the dark channel fog removal method based on dark color statistic priority can be applied to the fog removal of remote sensing images.
引文
[1]陶和平,刘斌涛,刘淑珍,等.遥感在重大自然灾害监测中的应用前景——以5·12汶川地震为例[J].山地学报,2008,26(3):276--279.
[2]Narasimhan S G,Nayar S K.Removing Weather Effects from Monochrome Images[C].Kauai:IEEE Computer Society Conference on Computer Vision and Pattern Recognition,2001.
[3]Narasimhan S G,Nayar S K.Contrast Restoration of Weather Degraded Images[J].IEEE Transactions on Pattern Analysis&Machine Intelligence,2003,25(6):713--724.
[4]贺辉,彭望琭,匡锦瑜.自适应滤波的高分辨率遥感影像薄云去除算法[J].地球信息科学学报,2009,11(3):305--311.
[5]叶秋果,宗景春,李钏,等.基于同态滤波的遥感影像去云雾处理[J].海洋测绘,2009,29(3):45--46.
[6]杨必武,郭晓松,王克军,等.基于直方图非线性拉伸的红外图像增强新算法[J].红外与激光工程,2003,32(1):1--3.
[7]殷年.基于线性拉伸的遥感图像处理[J].光电子技术与信息,1998,11(5):29--33.
[8]朱锡芳,徐芳芳.Retinex和小波变换去除遥感图像云雾方法分析[J].常州工学院学报,2007,20(5):8--13.
[9]He K,Sun J,Tang X.Single Image Haze Removal Using Dark Channel Prior[C].Miami:IEEE Conference on Computer Vision and Pattern Recognition,2009.
[2]Narasimhan S G,Nayar S K.Removing Weather Effects from Monochrome Images[C].Kauai:IEEE Computer Society Conference on Computer Vision and Pattern Recognition,2001.
[3]Narasimhan S G,Nayar S K.Contrast Restoration of Weather Degraded Images[J].IEEE Transactions on Pattern Analysis&Machine Intelligence,2003,25(6):713--724.
[4]贺辉,彭望琭,匡锦瑜.自适应滤波的高分辨率遥感影像薄云去除算法[J].地球信息科学学报,2009,11(3):305--311.
[5]叶秋果,宗景春,李钏,等.基于同态滤波的遥感影像去云雾处理[J].海洋测绘,2009,29(3):45--46.
[6]杨必武,郭晓松,王克军,等.基于直方图非线性拉伸的红外图像增强新算法[J].红外与激光工程,2003,32(1):1--3.
[7]殷年.基于线性拉伸的遥感图像处理[J].光电子技术与信息,1998,11(5):29--33.
[8]朱锡芳,徐芳芳.Retinex和小波变换去除遥感图像云雾方法分析[J].常州工学院学报,2007,20(5):8--13.
[9]He K,Sun J,Tang X.Single Image Haze Removal Using Dark Channel Prior[C].Miami:IEEE Conference on Computer Vision and Pattern Recognition,2009.