基于成像系统建模提高遥感图像分辨率方法研究
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摘要
随着全球信息化进程的飞速发展,军事和商业应用对高分辨率、高质量遥感图像的需求越来越迫切。但是由于探测器固有物理特性的限制,利用减小探测器像元尺寸、增加相机焦距等传统手段在提高空间分辨率方面取得新的突破越来越困难,成本越来越高。研究基于图像处理的方法以提高遥感图像的分辨率就成为一种有效可行的思路,具有重要的理论意义和应用价值。本文以基于成像建模理论的遥感图像分辨率提高方法为主线,针对遥感图像尤其是斜采样模式等亚像元技术中的分辨率分析、图像复原、超分辨率重建等方法进行研究,主要工作和研究成果如下：
(1)研究了光学遥感器的成像系统模型,建立了包括大气、卫星平台、光学系统、探测器、传感电路的成像模型,对造成遥感图像分辨率降低的因素进行了分析和讨论；从采样定理的角度分析了亚像元技术超分辨率重建的适用条件及能够提高分辨率的上限；指出利用亚像元采样技术提高遥感器的分辨率,可以充分利用光学系统的成像潜能,但是在不改变探测器像元尺寸和光学系统相对孔径的情况下,亚像元技术只能突破采样分辨率的极限,无限逼近系统光学衍射分辨率而不能超越这个极限。
(2)针对调制传递函数过零点问题,提出了一种单幅遥感图像频域校正超分辨率重建方法。由于卫星平台运动等因素的影响,调制传递函数在截止频率内存在大量过零点,这些过零点附近的噪声在图像复原过程中会被进一步放大甚至造成虚假的边缘和纹理。为了降低过零点对图像复原的不良影响,提出了一种频域校正方法,引入了遥感器有效载荷成像参数作为先验知识,将维纳滤波的结果作为全变分复原的初始值,通过对频域信息的校正,获得了更好的遥感图像超分辨率重建效果。
(3)混叠是影响采样式光学遥感器图像质量的重要因素之一。在分析了推扫式采样成像系统中的混叠形成原因的基础上,研究了基于模糊、混叠、噪声三元组的有效分辨率模型,通过对亚像元采样系统的有效分辨率进行定量计算和分析,指出了较为有效的采样；研究了单线阵斜采样模式和超模式斜采样模式中线阵倾斜角度及飞行方向采样间距对有效分辨率和成像质量的影响,得出了有效分辨率意义上的最佳成像参数。
(4)针对遥感图像中的混叠问题,提出了一种基于MAP-MRF的最佳倒易晶胞复原方法。通过对光学遥感图像存在模糊、混叠、噪声等三元退化因素成因的深入分析,建立了单线阵斜采样技术的最佳倒易晶胞模型,最大限度的获取斜采样模式下的图像有效信息。在MAP-MRF图像复原框架下,通过耦合有效分辨率最佳倒易晶胞,进一步减少了模糊、混叠、噪声对图像质量的影响,充分利用了由于混叠而错位的高频信息,获得了较好的复原效果；基于Majorization-Minimization的数值解法降低了计算复杂度,提高了运算速度和效率。
(5)针对超模式斜采样模式下的遥感图像重建问题,提出了一种新的超分辨率重建框架。由于超模式斜采样成像方式采用倾斜一定角度的两排CCD线阵,在传统超分辨率重建框架的基础上融合了纠偏策略。首先用Forstner算子提取图像特征点,采用基于粗细结合的匹配策略对图像序列进行刚性配准；然后在加入线阵倾斜角度的变换模型基础上,通过基于B样条的多帧图像插值方法得到高分辨率的初始图像；最后通过耦合最佳倒易晶胞的复原方法,建立了完整的超模式斜采样成像方式下的配准、插值、重建框架,有效地提高了超模式斜采样下的遥感图像的空间分辨率。
Remote sensing images are badly demanded for the military and commercial applications. The development of high resolution and good image quality sensors has become the main focus of earth observation technology. There are three traditional ways to improve spatial resolution: using smaller detector, increasing the camera focal length, reducing the satellite orbital altitude. But due to the inherent limitations of the physical properties, these methods are more and more difficult to achieve new breakthroughs. Image processing provides a new method to improve the remote sensing image resolution. The sub-pixel sampling technology is proved to be effective and feasible; meanwhile, the cost of is less expensive. This paper mainly focuses on the meth-ods of improving the image resolution, especially the effective resolution analysis of sub-pixel technology, image restoration and super resolution reconstruction.
(1) The optical remote sensing image system is studied. The image acquisition system includes the atmosphere, platform movement, optical system, detectors and noise. We analyzed the limits of the sub-pixel technology from the perspective of sampling theorem. Using sub-pixel technique can take advantage of the optical system. If the detector size and the optical system aperture are decided, the sub-pixel technology can only infinitely approximate to the system optical diffraction resolution but could not go beyond this limit.
(2) A novel single image super-resolution reconstruction method with frequency domain correction is proposed to solve the ill-posed problem imported by zero-crossing-points of mod-ulation transfer function (MTF). The satellite movement and some other factors bring lots of zero-crossing-points below the cut-off frequency. Noise near these zero-crossing-points would be amplified in the image restoration process, even cause false edges. To solve this problem, the geometrical characteristics of acquisition system are considered in the frequency domain cor-rection algorithm. In our method, the total variation restoration is used to revise the frequency spectral above the cut-off frequency; the wiener filter is used to initialize the TV restoration;the frequency domain correction can reduce the artifact caused by zero-crossing-points. Experi-mental results indicate that the proposed methods considering the modeling of image acqui-sition systems reconstruct high-quality super-resolution image for both composite image and remote sensing images with different physiognomy.
(3) Remote sensing image is degraded by a variety of factors. Aliasing is one of the important factors which affect the image quality of optical sampling remote sensing imaging system. After analyzing the aliasing-blurring-noise model in push-broom linear CCD imaging system, we quantitative calculated the aliasing, blurring and noise in sub-pixel sampling system with effective resolution. The tilting sampling mode includes the single linear tilting sampling and the super-mode tilting sampling. These two modes get a better resolution by rotating the CCD linear with a degree θ and/or reducing agent the sampling distance d. The impact of different parameters is discussed by calculating the effective resolution and optimal parameters are suggested.
(4) A novel image restoration method in the MAP-MRF frame is proposed to reduce the impact of aliasing and blurring. The optimal reciprocal cell is designed based on the effective resolution calculation. This optimal reciprocal cell is used to maximize the tilting sampling remote sensing image information. In the frame of MAP-MRF image restoration method, the optimal reciprocal cell is coupling with Huber-MRF image prior to reduce the blurring, aliasing and noise. After the restoration, the higher frequency part dislocated by sampling is corrected. A majorization-minimization approach is used to reduce the computational complexity. Exper-imental results indicate that the proposed method considers the modeling of image acquisition systems and obtains an effectives image restoration result, improves the image effective resolu-tion.
(5) Super-tilting mode improves the spatial resolution by rotating the two dedicated linear arrays with a degree. The bias-correct and interpolation is need to get uniformity image. The framework of super-tilting mode image super-resolution is built with registration, interpolation and deblurring. We use Forstner operator to extract image futures. Correlation is used to get a rough match, and then a distance constraint is used to remove the wrong matches. After the rigid registration, the angle of linear arrays is added into the transformation model, and a B-spline based interpolation is used to get the initial image of the high-resolution. Then we use the MAP based super-resolution reconstruction with optimal reciprocal cell to get the final result. Experimental results indicate that the proposed method reduces the aliasing in recovery and obtains an effectives image super-resolution restoration result.
(1)研究了光学遥感器的成像系统模型,建立了包括大气、卫星平台、光学系统、探测器、传感电路的成像模型,对造成遥感图像分辨率降低的因素进行了分析和讨论；从采样定理的角度分析了亚像元技术超分辨率重建的适用条件及能够提高分辨率的上限；指出利用亚像元采样技术提高遥感器的分辨率,可以充分利用光学系统的成像潜能,但是在不改变探测器像元尺寸和光学系统相对孔径的情况下,亚像元技术只能突破采样分辨率的极限,无限逼近系统光学衍射分辨率而不能超越这个极限。
(2)针对调制传递函数过零点问题,提出了一种单幅遥感图像频域校正超分辨率重建方法。由于卫星平台运动等因素的影响,调制传递函数在截止频率内存在大量过零点,这些过零点附近的噪声在图像复原过程中会被进一步放大甚至造成虚假的边缘和纹理。为了降低过零点对图像复原的不良影响,提出了一种频域校正方法,引入了遥感器有效载荷成像参数作为先验知识,将维纳滤波的结果作为全变分复原的初始值,通过对频域信息的校正,获得了更好的遥感图像超分辨率重建效果。
(3)混叠是影响采样式光学遥感器图像质量的重要因素之一。在分析了推扫式采样成像系统中的混叠形成原因的基础上,研究了基于模糊、混叠、噪声三元组的有效分辨率模型,通过对亚像元采样系统的有效分辨率进行定量计算和分析,指出了较为有效的采样；研究了单线阵斜采样模式和超模式斜采样模式中线阵倾斜角度及飞行方向采样间距对有效分辨率和成像质量的影响,得出了有效分辨率意义上的最佳成像参数。
(4)针对遥感图像中的混叠问题,提出了一种基于MAP-MRF的最佳倒易晶胞复原方法。通过对光学遥感图像存在模糊、混叠、噪声等三元退化因素成因的深入分析,建立了单线阵斜采样技术的最佳倒易晶胞模型,最大限度的获取斜采样模式下的图像有效信息。在MAP-MRF图像复原框架下,通过耦合有效分辨率最佳倒易晶胞,进一步减少了模糊、混叠、噪声对图像质量的影响,充分利用了由于混叠而错位的高频信息,获得了较好的复原效果；基于Majorization-Minimization的数值解法降低了计算复杂度,提高了运算速度和效率。
(5)针对超模式斜采样模式下的遥感图像重建问题,提出了一种新的超分辨率重建框架。由于超模式斜采样成像方式采用倾斜一定角度的两排CCD线阵,在传统超分辨率重建框架的基础上融合了纠偏策略。首先用Forstner算子提取图像特征点,采用基于粗细结合的匹配策略对图像序列进行刚性配准；然后在加入线阵倾斜角度的变换模型基础上,通过基于B样条的多帧图像插值方法得到高分辨率的初始图像；最后通过耦合最佳倒易晶胞的复原方法,建立了完整的超模式斜采样成像方式下的配准、插值、重建框架,有效地提高了超模式斜采样下的遥感图像的空间分辨率。
Remote sensing images are badly demanded for the military and commercial applications. The development of high resolution and good image quality sensors has become the main focus of earth observation technology. There are three traditional ways to improve spatial resolution: using smaller detector, increasing the camera focal length, reducing the satellite orbital altitude. But due to the inherent limitations of the physical properties, these methods are more and more difficult to achieve new breakthroughs. Image processing provides a new method to improve the remote sensing image resolution. The sub-pixel sampling technology is proved to be effective and feasible; meanwhile, the cost of is less expensive. This paper mainly focuses on the meth-ods of improving the image resolution, especially the effective resolution analysis of sub-pixel technology, image restoration and super resolution reconstruction.
(1) The optical remote sensing image system is studied. The image acquisition system includes the atmosphere, platform movement, optical system, detectors and noise. We analyzed the limits of the sub-pixel technology from the perspective of sampling theorem. Using sub-pixel technique can take advantage of the optical system. If the detector size and the optical system aperture are decided, the sub-pixel technology can only infinitely approximate to the system optical diffraction resolution but could not go beyond this limit.
(2) A novel single image super-resolution reconstruction method with frequency domain correction is proposed to solve the ill-posed problem imported by zero-crossing-points of mod-ulation transfer function (MTF). The satellite movement and some other factors bring lots of zero-crossing-points below the cut-off frequency. Noise near these zero-crossing-points would be amplified in the image restoration process, even cause false edges. To solve this problem, the geometrical characteristics of acquisition system are considered in the frequency domain cor-rection algorithm. In our method, the total variation restoration is used to revise the frequency spectral above the cut-off frequency; the wiener filter is used to initialize the TV restoration;the frequency domain correction can reduce the artifact caused by zero-crossing-points. Experi-mental results indicate that the proposed methods considering the modeling of image acqui-sition systems reconstruct high-quality super-resolution image for both composite image and remote sensing images with different physiognomy.
(3) Remote sensing image is degraded by a variety of factors. Aliasing is one of the important factors which affect the image quality of optical sampling remote sensing imaging system. After analyzing the aliasing-blurring-noise model in push-broom linear CCD imaging system, we quantitative calculated the aliasing, blurring and noise in sub-pixel sampling system with effective resolution. The tilting sampling mode includes the single linear tilting sampling and the super-mode tilting sampling. These two modes get a better resolution by rotating the CCD linear with a degree θ and/or reducing agent the sampling distance d. The impact of different parameters is discussed by calculating the effective resolution and optimal parameters are suggested.
(4) A novel image restoration method in the MAP-MRF frame is proposed to reduce the impact of aliasing and blurring. The optimal reciprocal cell is designed based on the effective resolution calculation. This optimal reciprocal cell is used to maximize the tilting sampling remote sensing image information. In the frame of MAP-MRF image restoration method, the optimal reciprocal cell is coupling with Huber-MRF image prior to reduce the blurring, aliasing and noise. After the restoration, the higher frequency part dislocated by sampling is corrected. A majorization-minimization approach is used to reduce the computational complexity. Exper-imental results indicate that the proposed method considers the modeling of image acquisition systems and obtains an effectives image restoration result, improves the image effective resolu-tion.
(5) Super-tilting mode improves the spatial resolution by rotating the two dedicated linear arrays with a degree. The bias-correct and interpolation is need to get uniformity image. The framework of super-tilting mode image super-resolution is built with registration, interpolation and deblurring. We use Forstner operator to extract image futures. Correlation is used to get a rough match, and then a distance constraint is used to remove the wrong matches. After the rigid registration, the angle of linear arrays is added into the transformation model, and a B-spline based interpolation is used to get the initial image of the high-resolution. Then we use the MAP based super-resolution reconstruction with optimal reciprocal cell to get the final result. Experimental results indicate that the proposed method reduces the aliasing in recovery and obtains an effectives image super-resolution restoration result.
引文
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