Space-based optical(SBO)space surveillance has attracted widespread interest in the last two decades due to its considerable value in space situation awareness(SSA).SBO observation strategy,which is related to the per...Space-based optical(SBO)space surveillance has attracted widespread interest in the last two decades due to its considerable value in space situation awareness(SSA).SBO observation strategy,which is related to the performance of space surveillance,is the top-level design in SSA missions reviewed.The recognized real programs about SBO SAA proposed by the institutions in the U.S.,Canada,Europe,etc.,are summarized firstly,from which an insight of the development trend of SBO SAA can be obtained.According to the aim of the SBO SSA,the missions can be divided into general surveillance and space object tracking.Thus,there are two major categories for SBO SSA strategies.Existing general surveillance strategies for observing low earth orbit(LEO)objects and beyond-LEO objects are summarized and compared in terms of coverage rate,revisit time,visibility period,and image processing.Then,the SBO space object tracking strategies,which has experienced from tracking an object with a single satellite to tracking an object with multiple satellites cooperatively,are also summarized.Finally,this paper looks into the development trend in the future and points out several problems that challenges the SBO SSA.展开更多
本文针对重载铁路线路关键区段夜间视频监控图像光照不足、对比度低、细节模糊等问题,提出了一种基于强度-正交色度颜色空间的改进图像亮度增强方法(Low Light Enhancement for Railway surveillance video image based on improved Col...本文针对重载铁路线路关键区段夜间视频监控图像光照不足、对比度低、细节模糊等问题,提出了一种基于强度-正交色度颜色空间的改进图像亮度增强方法(Low Light Enhancement for Railway surveillance video image based on improved Color space transform method,LLERC)。该方法首先将输入图像从RGB(Red,Green,Blue)颜色空间转换至所提出的改进IOC(Intensity-Orthometric-Chroma)颜色空间,以提取其强度和正交色度信息。随后,利用改进的轻量化双路U-net提取IOC颜色空间图像的特征,并预测实现亮度增强所需的强度残差和色度调整量。最后,将上述强度残差与输入图像叠加,得到光照增强后的IOC颜色空间图像,再将其转换为RGB颜色空间图像输出。将LLERC应用于重载铁路试验段,结果表明:LLERC方法在对比度、图像自然度、图像亮度顺序差异等指标上均优于传统图像增强方法和主流深度学习方法,并能有效提升重载铁路夜间视频监控图像的清晰度和自然程度。展开更多
基金This work was supported by the National Natural Science Foundation of China(61690210,61690213).
文摘Space-based optical(SBO)space surveillance has attracted widespread interest in the last two decades due to its considerable value in space situation awareness(SSA).SBO observation strategy,which is related to the performance of space surveillance,is the top-level design in SSA missions reviewed.The recognized real programs about SBO SAA proposed by the institutions in the U.S.,Canada,Europe,etc.,are summarized firstly,from which an insight of the development trend of SBO SAA can be obtained.According to the aim of the SBO SSA,the missions can be divided into general surveillance and space object tracking.Thus,there are two major categories for SBO SSA strategies.Existing general surveillance strategies for observing low earth orbit(LEO)objects and beyond-LEO objects are summarized and compared in terms of coverage rate,revisit time,visibility period,and image processing.Then,the SBO space object tracking strategies,which has experienced from tracking an object with a single satellite to tracking an object with multiple satellites cooperatively,are also summarized.Finally,this paper looks into the development trend in the future and points out several problems that challenges the SBO SSA.
文摘本文针对重载铁路线路关键区段夜间视频监控图像光照不足、对比度低、细节模糊等问题,提出了一种基于强度-正交色度颜色空间的改进图像亮度增强方法(Low Light Enhancement for Railway surveillance video image based on improved Color space transform method,LLERC)。该方法首先将输入图像从RGB(Red,Green,Blue)颜色空间转换至所提出的改进IOC(Intensity-Orthometric-Chroma)颜色空间,以提取其强度和正交色度信息。随后,利用改进的轻量化双路U-net提取IOC颜色空间图像的特征,并预测实现亮度增强所需的强度残差和色度调整量。最后,将上述强度残差与输入图像叠加,得到光照增强后的IOC颜色空间图像,再将其转换为RGB颜色空间图像输出。将LLERC应用于重载铁路试验段,结果表明:LLERC方法在对比度、图像自然度、图像亮度顺序差异等指标上均优于传统图像增强方法和主流深度学习方法,并能有效提升重载铁路夜间视频监控图像的清晰度和自然程度。
