受云雾干扰的可见光遥感影像信息补偿技术研究
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摘要
20世纪80年代以来,计算机技术、通讯技术和遥感技术的飞速发展给遥感图像处理等技术带来了新的发展契机。遥感图像凭借其覆盖范围广和具有较高的多种分辨率等特点也被广泛应用于国土资源调查、基础地理信息获取、城市规划、农业生产、海洋监测、气象观测及天文发现等各个领域。然而,受传感器自身特性的限制,目前除主动式的雷达摄影能有效地避免复杂天气的影响外,几乎所有借助被动式光学遥感手段获取的影像都不同程度地受到云、雾、霭等天气的干扰,这种干扰已经成为遥感图像在各领域应用中的主要障碍,尤其影响了基于遥感图像的测绘产品生产,延长了作业时间并使生产效率降低。
基于单幅遥感图像进行图像清晰化处理及利用辅助图像进行厚云区域的信息补偿能够有效地提升遥感图像质量、提高遥感图像的利用率。本文针对遥感对地观测中常用的光学遥感图像,结合摄影测量、计算机视觉、图像处理及图论等领域的最新理论,分别对薄云去除及厚云区域信息补偿的若干理论与算法进行了深入研究,设计实现了一套实用的软件应用系统,并成功应用于陆地特定区域及海岛(礁)区域的影像处理。
论文的主要研究内容及创新点概括如下:
1.总结并分析了云雾图像的电磁波谱特征、纹理特征、空间分布特征及地物间的相关特征。由于云雾图像成像时,薄云和厚云的四种成像特征差异较大,图像退化模型也大不相同,薄云退化图像信号包含电磁波经云层反射和电磁波经地面反射及云层透射综合作用的两部分信号,而厚云退化图像在云覆盖区域仅包含云层反射信号,这从根本上决定了两种云覆盖图像处理方法将有所不同。上述分析为后续的算法研究提供了必要的理论支持。
2.总结并分析了经典的去薄云算法的基本原理,例如直方图增强法、同态滤波法、小波变换法及暗原色法,对涉及的小波变换法进行了深入的研究比较。由于小波家族中小波函数和小波变换方法千差万别,致使小波分析在图像去云中的应用存在诸多困惑。本文针对不同的小波基函数、不同的分解层数和不同的小波方法进行了实验分析。实验表明:具有近似对称的db4小波和sym6小波处理效果较好,结果图像中完全没有马赛克现象,并且在地物边缘处没有移位发生;平稳小波变换适用于3层小波分解,小波包变换适用2层小波包分解,而提升小波只须1层小波分解就能达到理想的效果;提升小波变换及平稳小波变换能够做为去云的小波变换方法。综合上述分析认为,以db4小波做为小波基的1层提升小波变换是薄云去除小波变换算法中的最优选择,以db4小波做为小波基的3层平稳小波变换的薄云去除方法次之。
3.提出了一种针对非均匀分布的薄云图像清晰化复原方法。该算法利用高斯滤波器的低通特性,对成像时刻的云雾浓度进行了自动估计,改进了云雾图像的退化公式,将退化模型中大气光估计值赋予云雾浓度信息,有效避免了图像清晰化过程中出现的“欠处理”或“过处理”现象。利用不同分辨率的两幅图像进行实验验证,实验结果表明,针对非均匀分布的云雾图像的清晰化算法复原处理后的图像,其各项评价指标均优于暗原色去云雾算法。
4.地物影像替换去云法是简单且直接有效的遥感图像厚云去除方法。但是由于影像间的差异,影像替换后极易产生类似“拼接缝”的现象,本文利用灰度统计及Freeman链码轮廓跟踪技术引导云层及云影的自动识别,然后巧妙选取云及阴影区域的最小外接矩形做为地物替换区域,结合直方图匹配和数学形态学理论,提出了无缝化的遥感图像厚云区域信息补偿方案,该方案在实际生产应用中产生了较好的处理效果。
5.把图割理论中的最大流最小割思想引入到图像匀光算法中,将水域与陆地区域进行区分处理,有效地避免了因水域的镜面反射作用对整幅图像匀光效果的影响。实验表明,与基于梯度域以及基于分裂合并的图像匀光算法相比,基于图割理论的匀光算法具有更好的稳定性和自适应性,能够取得更为令人满意的匀光效果。
6.将上述多种算法综合应用于海岛(礁)区域及我国西南地区的遥感影像处理,结合具体工程实践,验证了理论和算法的合理性和有效性。
The rapid development of computer, communication and remote sensing techniques has brought new opportunities for the remote sensing image processing since the 1980’s. By virtue of its wide area coverage and various spatial resolution, remote sensing image has been widely used in different fields, including land resource investigation, basic geographic information acquisition, city planning, agricultural production, oceanographic monitor, meteorological observation and astronomical discovery. However, except active radar photography can effectively avoid the weather disturbance, almost all remote sensing images obtained in the passive optical means are subject to different levels of clouds, mist and brume’s influence, and this interference has been the major obstacles for the widespread use of remote sensing image, especially for the mapping production based on remote sensing image, prolonging the production time and lower productivity.
The quality and utilization of remote sensing image can be greatly improved when the clearness processing is performed based on single image and information compensation related to the thick cloud area is achieved based on auxiliary image. Aiming at the optical image commonly used in the earth observation, with the latest theories of photogrammetry, computer vision, image processing and graph theory, this thesis made an intensive and deep study on the theories and approaches of haze removal and information compensation related to the cirrus area, designed and completed a practical application software which has successfully been applied to the image processing on specific land areas and island areas.
The main contents and innovations in this thesis can be summarized as follows.
1. The electromagnetic spectrum features, textural features, spatial distribution features and correlation features in degraded cloudy images are summarized and analyzed. The haze image is made up of two signals, reflected electromagnetic wave signal from haze and ground, transmission electromagnetic wave from haze, and that degraded image with thick cloud only includes cloud reflected signal. These different degradation models determine two kinds of image processing methods. Above-analysis offers the essential theoretical supports for the study of subsequent algorithms.
2. The main principles and fundamentals of classical haze removal algorithms are summarized and analyzed, which include histogram enhancement, homomorphic filtering, wavelet transformation, and dark channel prior dehazing. Then we conducted in-depth study of wavelet transform. There are many kinds of wavelet functions and transformations, which bring much trouble to the study of cloud removing in RS image. In this thesis, various types of wavelet base functions, decomposition layers and kernel methods are conducted and tested. The experimental results show that, db4 and sym6 wavelet functions with approximately symmetry provide better results in which the Mosaic Show has been eliminated entirely and no displacements at object’s edges occurs. DSWT is applicable to three layers decompositions, and wavelet packets is suitable for two layers decompositions. Just one layer decomposition can produce the ideal results when the lifting wavelet is used. The lifting wavelet transform and stationary wavelet transform are fit for cloud removing process. From the above comprehensive analysis, the lifting wavelet transform using the db4 wavelet function and one layer decomposition is considered to be the optimal selection for haze removal, and the stationary wavelet transform using the db4 wavelet function and with three layer decompositions is the secondary selection.
3. A clearness improvement method for image with non-uniform cloud and mist distribution is proposed. In this method, the density of cloud and mist is automatically evaluated based on the low pass characteristics of Gaussian Filter. Then the degraded equation of cloudy and misty image is improved, which avoid“under-processing”and“over-processing”in the clearness improvement. Finally, two images with different resolutions are used to verify the experiment. Experimental results indicate that the clearness improvement method presented in this thesis for the image with non-uniform cloud and mist distribution takes advantage over dark channel prior method in each evaluating indicator.
4. Direct-replacing method is a simple and effective cloud removing method for the remote sensing images. This method substitutes the cloudy pixels with the corresponding pixels on the auxiliary image. But it inclines to cause obvious seam lines between substituted cloud area and original image. In this thesis, the replace area is skillfully selected firstly. Then combined with histogram theory and mathematical morphology theory, the scheme for the seamless information compensation related to the cloud area is discussed, which achieves good effects in the practical production application.
5. By applying Min-cut/Max-flow of graph theory to the image dodging algorithm, water area and terrestrial area can be processes separately, which effectively avoids the water specular reflection effect. Experiments show that, compared with the algorithms based on Split-Merge and gradient field, the dodging algorithm based on the graph theory can achieve a more satisfactory results.
6. The above algorithms are applied to the remote sensing image processing in islands areas and the southwest of china areas. Moreover, the rationality and effectiveness of the algorithms are verified in real projects. Key words: Information Compensation, Homomorphic Filtering, Wavelet Transformation, Non-uniform Cloud, Image Registration, Image Fusion, Graph Cut, Image Dodging Processing
基于单幅遥感图像进行图像清晰化处理及利用辅助图像进行厚云区域的信息补偿能够有效地提升遥感图像质量、提高遥感图像的利用率。本文针对遥感对地观测中常用的光学遥感图像,结合摄影测量、计算机视觉、图像处理及图论等领域的最新理论,分别对薄云去除及厚云区域信息补偿的若干理论与算法进行了深入研究,设计实现了一套实用的软件应用系统,并成功应用于陆地特定区域及海岛(礁)区域的影像处理。
论文的主要研究内容及创新点概括如下:
1.总结并分析了云雾图像的电磁波谱特征、纹理特征、空间分布特征及地物间的相关特征。由于云雾图像成像时,薄云和厚云的四种成像特征差异较大,图像退化模型也大不相同,薄云退化图像信号包含电磁波经云层反射和电磁波经地面反射及云层透射综合作用的两部分信号,而厚云退化图像在云覆盖区域仅包含云层反射信号,这从根本上决定了两种云覆盖图像处理方法将有所不同。上述分析为后续的算法研究提供了必要的理论支持。
2.总结并分析了经典的去薄云算法的基本原理,例如直方图增强法、同态滤波法、小波变换法及暗原色法,对涉及的小波变换法进行了深入的研究比较。由于小波家族中小波函数和小波变换方法千差万别,致使小波分析在图像去云中的应用存在诸多困惑。本文针对不同的小波基函数、不同的分解层数和不同的小波方法进行了实验分析。实验表明:具有近似对称的db4小波和sym6小波处理效果较好,结果图像中完全没有马赛克现象,并且在地物边缘处没有移位发生;平稳小波变换适用于3层小波分解,小波包变换适用2层小波包分解,而提升小波只须1层小波分解就能达到理想的效果;提升小波变换及平稳小波变换能够做为去云的小波变换方法。综合上述分析认为,以db4小波做为小波基的1层提升小波变换是薄云去除小波变换算法中的最优选择,以db4小波做为小波基的3层平稳小波变换的薄云去除方法次之。
3.提出了一种针对非均匀分布的薄云图像清晰化复原方法。该算法利用高斯滤波器的低通特性,对成像时刻的云雾浓度进行了自动估计,改进了云雾图像的退化公式,将退化模型中大气光估计值赋予云雾浓度信息,有效避免了图像清晰化过程中出现的“欠处理”或“过处理”现象。利用不同分辨率的两幅图像进行实验验证,实验结果表明,针对非均匀分布的云雾图像的清晰化算法复原处理后的图像,其各项评价指标均优于暗原色去云雾算法。
4.地物影像替换去云法是简单且直接有效的遥感图像厚云去除方法。但是由于影像间的差异,影像替换后极易产生类似“拼接缝”的现象,本文利用灰度统计及Freeman链码轮廓跟踪技术引导云层及云影的自动识别,然后巧妙选取云及阴影区域的最小外接矩形做为地物替换区域,结合直方图匹配和数学形态学理论,提出了无缝化的遥感图像厚云区域信息补偿方案,该方案在实际生产应用中产生了较好的处理效果。
5.把图割理论中的最大流最小割思想引入到图像匀光算法中,将水域与陆地区域进行区分处理,有效地避免了因水域的镜面反射作用对整幅图像匀光效果的影响。实验表明,与基于梯度域以及基于分裂合并的图像匀光算法相比,基于图割理论的匀光算法具有更好的稳定性和自适应性,能够取得更为令人满意的匀光效果。
6.将上述多种算法综合应用于海岛(礁)区域及我国西南地区的遥感影像处理,结合具体工程实践,验证了理论和算法的合理性和有效性。
The rapid development of computer, communication and remote sensing techniques has brought new opportunities for the remote sensing image processing since the 1980’s. By virtue of its wide area coverage and various spatial resolution, remote sensing image has been widely used in different fields, including land resource investigation, basic geographic information acquisition, city planning, agricultural production, oceanographic monitor, meteorological observation and astronomical discovery. However, except active radar photography can effectively avoid the weather disturbance, almost all remote sensing images obtained in the passive optical means are subject to different levels of clouds, mist and brume’s influence, and this interference has been the major obstacles for the widespread use of remote sensing image, especially for the mapping production based on remote sensing image, prolonging the production time and lower productivity.
The quality and utilization of remote sensing image can be greatly improved when the clearness processing is performed based on single image and information compensation related to the thick cloud area is achieved based on auxiliary image. Aiming at the optical image commonly used in the earth observation, with the latest theories of photogrammetry, computer vision, image processing and graph theory, this thesis made an intensive and deep study on the theories and approaches of haze removal and information compensation related to the cirrus area, designed and completed a practical application software which has successfully been applied to the image processing on specific land areas and island areas.
The main contents and innovations in this thesis can be summarized as follows.
1. The electromagnetic spectrum features, textural features, spatial distribution features and correlation features in degraded cloudy images are summarized and analyzed. The haze image is made up of two signals, reflected electromagnetic wave signal from haze and ground, transmission electromagnetic wave from haze, and that degraded image with thick cloud only includes cloud reflected signal. These different degradation models determine two kinds of image processing methods. Above-analysis offers the essential theoretical supports for the study of subsequent algorithms.
2. The main principles and fundamentals of classical haze removal algorithms are summarized and analyzed, which include histogram enhancement, homomorphic filtering, wavelet transformation, and dark channel prior dehazing. Then we conducted in-depth study of wavelet transform. There are many kinds of wavelet functions and transformations, which bring much trouble to the study of cloud removing in RS image. In this thesis, various types of wavelet base functions, decomposition layers and kernel methods are conducted and tested. The experimental results show that, db4 and sym6 wavelet functions with approximately symmetry provide better results in which the Mosaic Show has been eliminated entirely and no displacements at object’s edges occurs. DSWT is applicable to three layers decompositions, and wavelet packets is suitable for two layers decompositions. Just one layer decomposition can produce the ideal results when the lifting wavelet is used. The lifting wavelet transform and stationary wavelet transform are fit for cloud removing process. From the above comprehensive analysis, the lifting wavelet transform using the db4 wavelet function and one layer decomposition is considered to be the optimal selection for haze removal, and the stationary wavelet transform using the db4 wavelet function and with three layer decompositions is the secondary selection.
3. A clearness improvement method for image with non-uniform cloud and mist distribution is proposed. In this method, the density of cloud and mist is automatically evaluated based on the low pass characteristics of Gaussian Filter. Then the degraded equation of cloudy and misty image is improved, which avoid“under-processing”and“over-processing”in the clearness improvement. Finally, two images with different resolutions are used to verify the experiment. Experimental results indicate that the clearness improvement method presented in this thesis for the image with non-uniform cloud and mist distribution takes advantage over dark channel prior method in each evaluating indicator.
4. Direct-replacing method is a simple and effective cloud removing method for the remote sensing images. This method substitutes the cloudy pixels with the corresponding pixels on the auxiliary image. But it inclines to cause obvious seam lines between substituted cloud area and original image. In this thesis, the replace area is skillfully selected firstly. Then combined with histogram theory and mathematical morphology theory, the scheme for the seamless information compensation related to the cloud area is discussed, which achieves good effects in the practical production application.
5. By applying Min-cut/Max-flow of graph theory to the image dodging algorithm, water area and terrestrial area can be processes separately, which effectively avoids the water specular reflection effect. Experiments show that, compared with the algorithms based on Split-Merge and gradient field, the dodging algorithm based on the graph theory can achieve a more satisfactory results.
6. The above algorithms are applied to the remote sensing image processing in islands areas and the southwest of china areas. Moreover, the rationality and effectiveness of the algorithms are verified in real projects. Key words: Information Compensation, Homomorphic Filtering, Wavelet Transformation, Non-uniform Cloud, Image Registration, Image Fusion, Graph Cut, Image Dodging Processing
引文
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