航天光学遥感器图像终端像质评价方法研究
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摘要
航天光学遥感器是搭载在卫星或航天飞行器上的利用光学技术获取目标属性和相关信息的精密科学设备。该设备由于搭载在卫星或航天飞行器上工作，因此具有以下一些独特优势：工作在真空环境中，远离大气环境的干扰，有利于光学遥感器的清晰成像；工作范围不受地域限制，可以对全球或外太空任意感兴趣目标进行观测；工作时间不受限制，可以在任何预定时间工作；获取的遥感数据应用领域广泛，如军事侦察、环境资源评估、自然灾害评估、气象研究等。
航天光学遥感器的成像质量是遥感器的关键技术指标，遥感器能否产生高质量的遥感图像直接关系到整个航天光学遥感任务的成败。因此长期以来航天光学遥感器的像质评价工作一直受到研究人员的高度重视。光学遥感器的像质评价工作不但可以定量表征遥感器的成像质量，而且可以指导地面装调工作，有利于提高光学遥感器的地面装调水平。另外通过对在轨遥感器成像质量的长期监测，可以深入分析影响遥感器成像质量和寿命的各种因素，有利于遥感器设计技术的改进和进步。
本文主要研究可见光波段的具有详查功能的航天光学遥感器整机像质评价方法。传统的遥感器整机像质评价方法有鉴别率板法、矩形空间频率靶板测调制传递函数法等等，但是这些测试方法随着光学遥感器研制技术的发展与技术要求的提高正在面临新的挑战。目前可见光波段具有详查功能的光学遥感器的光学口径越来越大、焦距越来越长、地面分辨率越来越高、体积重量越来越大，这些变化使传统的整机像质评价方法受到了测试场地、测试环境和测试设备的限制。例如大口径长焦距遥感器像质测试时，测试场地的温度、振动水平难以控制，平行光管设备、积分球设备研制加工困难，高空间频率的矩形靶板制作困难等等。
本文针对航天光学遥感器整机像质评价工作面临的挑战，提出了应用航天光学遥感器的图像终端进行遥感器整机像质评价的新思路。即通过对光学遥感器获取的遥感器图像产品的图像质量评价间接的实现遥感器整机像质评价。遥感图像的图像质量不但反映了遥感器自身的成像性能，而且综合了遥感器应用技术水平的高低。因此遥感图像的图像质量综合反映光学遥感器从光信息收集到像移补偿、光电转换、数字信号处理、压缩、存储等全链路过程的质量水平，同时也最真实的表征了光学遥感器的整机成像性能。通过这种方法评价遥感器整机成像性能不但不受测试设备、场地、环境的限制，而且能够实现遥感器成像质量的在轨实时监测。
为了评价遥感图像的图像质量，本文从两个不同角度开展了图像质量评价的研究工作。
一种方法是以常用的光学调制传递函数作为图像质量的评价参量，通过改进的BP神经网络实现遥感器图像在奈奎斯特频率处MTF的估计。该方法中神经网络的输入参量为从图像中提取的能够表征图像MTF水平的特征参量。本文详细论述了可控MTF的遥感图像仿真方法、表征图像MTF水平的特征参量的提取方法、神经网络模型的设计及模型参数的确定方法，以及神经网络估计遥感图像MTF的精度水平。
另一种方法将退化的遥感图像与“理想自然”遥感图像模型参数之间的“距离”作为遥感图像质量的度量。该方法是一种基于自然场景统计理论的无参考图像质量评价方法，认为“理想自然”的遥感图像具有某种不变的统计模型参数，而经过成像设备获取的遥感图像在各种退化作用下（如模糊、噪声、压缩等等）这种统计模型参数将发生改变。本文详细论述了图像的特征参量选取方法、图像统计模型的建立方法，以及如何度量图像统计模型参数间的“距离”等问题，最后对该方法与主观评价图像方法的相关性进行了研究，并应用该方法进行了实际的遥感图像像质评价实验，进一步证实了应用该方法进行遥感图像像质评价的有效性。
实验结果表明，两种遥感图像像质评价方法研究思路是正确可行的，并且图像质量评价可以达到一定的精度要求，图像质量的评价结果与人对图像质量的主观感受相一致。同时本论文的研究为进一步通过遥感图像质量表征遥感器整机成像水平的研究工作奠定了基础。
Spaceborne optical remote sensor is a precision scientific instrument carried onsatellites or shuttles, which can obtain the optical attributes and related informationabout the target. It has the following advantages due to working on various satelliteplatform: working in vacuum environment, far away from atmosphere environment,which will benefit to clear image; the imaging task is not subject to regionalrestriction, which can achieve to observe the interested target in global or outer space;the working time is flexible, which can work in any of the scheduled time for remotesensing; the data obtained by the remote sensor are widely used in many fields such asmilitary reconnaissance, environmental resources assessment, natural disasterassessment, and weather forecast.
Imagery quality of spaceborne optical remote sensor is a key test item, whetherremote sensor can produce high quality remote sensing imagery is directly linked tothe success or failure of the remote sensing tasks. So the imaging quality assessmentof spaceborne remote sensor has a vital significance for a long time. The work,assessing the spaceborne optical remote sensing imagery quality, not only canquantitatively characterize the imaging quality of spaceborne remote sensor, but alsocan provide assistance for ground assembly and promote the technology of groundassembly. In the meantime, through the work of monitoring the remote sensor imaging quality on orbit for the long time, the factors of impact the remote sensorimaging quality and lifetime can be analyzed, it also can help promoting andimproving the design technology of remote sensor.
The methods of imaging quality assessment were researched in this dissertation.The spaceborne optical remote sensor we researched is working in the visible lightwaveband with the function of detailed observation. There are many traditionalmethods for remote sensor imaging quality assessment, such as resolution test patternmethod, using rectangular spatial frequency target plates to measure modulationtransfer function, and so on. But these methods face some new challenges with theoptical remote sensor research technology development and the improvement of thetechnical requirements. Nowadays the optical remote sensors working in visible lightwaveband with the function of detailed observation have some new trends: the opticaldiameter is increasing, the focal length is getting longer, the ground resolution isgetting higher, and the volume and weight is growing larger. The new trends make thetraditional methods of imaging quality assessment limit by the test site, testenvironment and test equipment. For example, the temperature and vibration level ofthe test site meeting the imaging quality assessment for large diameter and long focallength optical remote sensor is difficult to control. And the collimator devices, thehigh spatial frequency rectangular target and the integrating sphere apparatus aredifficult to be manufactured.
In this dissertation, the novel idea, applying the spaceborne optical remote sensorimage terminal quality to assess the imaging performance of remote sensor, wasproposed. It can realize to assess spaceborne optical remote sensor imagingperformance through the quality of image terminal. The imagery quality cancharacterize not only the imaging performance of the spaceborne remote sensor, butalso the imaging technology. Therefore, the imagery quality we assessed synthesizesthe whole factors which degenerate the imagery in imaging chain, such as obtainingoptical information, compensation of image motion, photoelectric conversion, digitalsignal processing, storage, compression and so on. Assessment the imaging quality ofremote sensor by this method can realize monitoring the imaging quality of remote sensor on orbit, and it is not constrained by the test equipment, test site and testenvironment.
In order to assess the imagery quality of spaceborne optical remote sensor, theresearch methods of imagery quality assessment taken from two different perspectiveswere proposed.
One is using the optical modulation transfer function as imagery quality index,the MTF of remote imagery at Nyquist frequency was estimated by the improved BPneural network. The input parameters of the neural network are extracted from theimagery obtained by the remote sensor. This paper discusses in detail as follows: thesimulation method of remote sensing imagery with controlled MTF, the extractionmethod of parameters which can characterize the MTF level of remote sensingimagery, the model designing and parameters determination method of the neuralnetwork, and the accuracy of imagery quality assessed by neural network.
The other one is using the distance of parameters model between ideal naturalimagery and degraded imagery as quality metrics. The method is based on the theoryof statistical natural scenes, which is a no reference image quality assessment method.By the theory of statistical natural scenes, it is believed that ideal natural scenesimagery have some unchanged statistical model parameters, and the parameters willbe changed along with the image degrading by noise, compression, blur and so on.The follows were discussed in detail: the select method of image characteristicparameters, the design method of statistical model, and how to measure the distanceof the statistical model parameters, in the end the correlation between this method andsubjective image quality assessment method was researched.
The experimental results show that the ideas of two remote sensing image qualityassessment methods are feasible, the assessment results have a reasonable accuracy,and the results can better reflect the subjective feelings of the image quality. Thisthesis laid the foundation for the further research about remote sensor imagingperformance characterized by the remote image quality.
航天光学遥感器的成像质量是遥感器的关键技术指标，遥感器能否产生高质量的遥感图像直接关系到整个航天光学遥感任务的成败。因此长期以来航天光学遥感器的像质评价工作一直受到研究人员的高度重视。光学遥感器的像质评价工作不但可以定量表征遥感器的成像质量，而且可以指导地面装调工作，有利于提高光学遥感器的地面装调水平。另外通过对在轨遥感器成像质量的长期监测，可以深入分析影响遥感器成像质量和寿命的各种因素，有利于遥感器设计技术的改进和进步。
本文主要研究可见光波段的具有详查功能的航天光学遥感器整机像质评价方法。传统的遥感器整机像质评价方法有鉴别率板法、矩形空间频率靶板测调制传递函数法等等，但是这些测试方法随着光学遥感器研制技术的发展与技术要求的提高正在面临新的挑战。目前可见光波段具有详查功能的光学遥感器的光学口径越来越大、焦距越来越长、地面分辨率越来越高、体积重量越来越大，这些变化使传统的整机像质评价方法受到了测试场地、测试环境和测试设备的限制。例如大口径长焦距遥感器像质测试时，测试场地的温度、振动水平难以控制，平行光管设备、积分球设备研制加工困难，高空间频率的矩形靶板制作困难等等。
本文针对航天光学遥感器整机像质评价工作面临的挑战，提出了应用航天光学遥感器的图像终端进行遥感器整机像质评价的新思路。即通过对光学遥感器获取的遥感器图像产品的图像质量评价间接的实现遥感器整机像质评价。遥感图像的图像质量不但反映了遥感器自身的成像性能，而且综合了遥感器应用技术水平的高低。因此遥感图像的图像质量综合反映光学遥感器从光信息收集到像移补偿、光电转换、数字信号处理、压缩、存储等全链路过程的质量水平，同时也最真实的表征了光学遥感器的整机成像性能。通过这种方法评价遥感器整机成像性能不但不受测试设备、场地、环境的限制，而且能够实现遥感器成像质量的在轨实时监测。
为了评价遥感图像的图像质量，本文从两个不同角度开展了图像质量评价的研究工作。
一种方法是以常用的光学调制传递函数作为图像质量的评价参量，通过改进的BP神经网络实现遥感器图像在奈奎斯特频率处MTF的估计。该方法中神经网络的输入参量为从图像中提取的能够表征图像MTF水平的特征参量。本文详细论述了可控MTF的遥感图像仿真方法、表征图像MTF水平的特征参量的提取方法、神经网络模型的设计及模型参数的确定方法，以及神经网络估计遥感图像MTF的精度水平。
另一种方法将退化的遥感图像与“理想自然”遥感图像模型参数之间的“距离”作为遥感图像质量的度量。该方法是一种基于自然场景统计理论的无参考图像质量评价方法，认为“理想自然”的遥感图像具有某种不变的统计模型参数，而经过成像设备获取的遥感图像在各种退化作用下（如模糊、噪声、压缩等等）这种统计模型参数将发生改变。本文详细论述了图像的特征参量选取方法、图像统计模型的建立方法，以及如何度量图像统计模型参数间的“距离”等问题，最后对该方法与主观评价图像方法的相关性进行了研究，并应用该方法进行了实际的遥感图像像质评价实验，进一步证实了应用该方法进行遥感图像像质评价的有效性。
实验结果表明，两种遥感图像像质评价方法研究思路是正确可行的，并且图像质量评价可以达到一定的精度要求，图像质量的评价结果与人对图像质量的主观感受相一致。同时本论文的研究为进一步通过遥感图像质量表征遥感器整机成像水平的研究工作奠定了基础。
Spaceborne optical remote sensor is a precision scientific instrument carried onsatellites or shuttles, which can obtain the optical attributes and related informationabout the target. It has the following advantages due to working on various satelliteplatform: working in vacuum environment, far away from atmosphere environment,which will benefit to clear image; the imaging task is not subject to regionalrestriction, which can achieve to observe the interested target in global or outer space;the working time is flexible, which can work in any of the scheduled time for remotesensing; the data obtained by the remote sensor are widely used in many fields such asmilitary reconnaissance, environmental resources assessment, natural disasterassessment, and weather forecast.
Imagery quality of spaceborne optical remote sensor is a key test item, whetherremote sensor can produce high quality remote sensing imagery is directly linked tothe success or failure of the remote sensing tasks. So the imaging quality assessmentof spaceborne remote sensor has a vital significance for a long time. The work,assessing the spaceborne optical remote sensing imagery quality, not only canquantitatively characterize the imaging quality of spaceborne remote sensor, but alsocan provide assistance for ground assembly and promote the technology of groundassembly. In the meantime, through the work of monitoring the remote sensor imaging quality on orbit for the long time, the factors of impact the remote sensorimaging quality and lifetime can be analyzed, it also can help promoting andimproving the design technology of remote sensor.
The methods of imaging quality assessment were researched in this dissertation.The spaceborne optical remote sensor we researched is working in the visible lightwaveband with the function of detailed observation. There are many traditionalmethods for remote sensor imaging quality assessment, such as resolution test patternmethod, using rectangular spatial frequency target plates to measure modulationtransfer function, and so on. But these methods face some new challenges with theoptical remote sensor research technology development and the improvement of thetechnical requirements. Nowadays the optical remote sensors working in visible lightwaveband with the function of detailed observation have some new trends: the opticaldiameter is increasing, the focal length is getting longer, the ground resolution isgetting higher, and the volume and weight is growing larger. The new trends make thetraditional methods of imaging quality assessment limit by the test site, testenvironment and test equipment. For example, the temperature and vibration level ofthe test site meeting the imaging quality assessment for large diameter and long focallength optical remote sensor is difficult to control. And the collimator devices, thehigh spatial frequency rectangular target and the integrating sphere apparatus aredifficult to be manufactured.
In this dissertation, the novel idea, applying the spaceborne optical remote sensorimage terminal quality to assess the imaging performance of remote sensor, wasproposed. It can realize to assess spaceborne optical remote sensor imagingperformance through the quality of image terminal. The imagery quality cancharacterize not only the imaging performance of the spaceborne remote sensor, butalso the imaging technology. Therefore, the imagery quality we assessed synthesizesthe whole factors which degenerate the imagery in imaging chain, such as obtainingoptical information, compensation of image motion, photoelectric conversion, digitalsignal processing, storage, compression and so on. Assessment the imaging quality ofremote sensor by this method can realize monitoring the imaging quality of remote sensor on orbit, and it is not constrained by the test equipment, test site and testenvironment.
In order to assess the imagery quality of spaceborne optical remote sensor, theresearch methods of imagery quality assessment taken from two different perspectiveswere proposed.
One is using the optical modulation transfer function as imagery quality index,the MTF of remote imagery at Nyquist frequency was estimated by the improved BPneural network. The input parameters of the neural network are extracted from theimagery obtained by the remote sensor. This paper discusses in detail as follows: thesimulation method of remote sensing imagery with controlled MTF, the extractionmethod of parameters which can characterize the MTF level of remote sensingimagery, the model designing and parameters determination method of the neuralnetwork, and the accuracy of imagery quality assessed by neural network.
The other one is using the distance of parameters model between ideal naturalimagery and degraded imagery as quality metrics. The method is based on the theoryof statistical natural scenes, which is a no reference image quality assessment method.By the theory of statistical natural scenes, it is believed that ideal natural scenesimagery have some unchanged statistical model parameters, and the parameters willbe changed along with the image degrading by noise, compression, blur and so on.The follows were discussed in detail: the select method of image characteristicparameters, the design method of statistical model, and how to measure the distanceof the statistical model parameters, in the end the correlation between this method andsubjective image quality assessment method was researched.
The experimental results show that the ideas of two remote sensing image qualityassessment methods are feasible, the assessment results have a reasonable accuracy,and the results can better reflect the subjective feelings of the image quality. Thisthesis laid the foundation for the further research about remote sensor imagingperformance characterized by the remote image quality.
引文
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