This paper elaborated the role of color composition in plant landscape design of Chicago Botanic Garden systematically, used examples to analyze color design of plant landscapes in the garden, and the specifi c applic...This paper elaborated the role of color composition in plant landscape design of Chicago Botanic Garden systematically, used examples to analyze color design of plant landscapes in the garden, and the specifi c application of color contrast in wall plant decoration, courtyard waterscape, indoor greenhouse and tree decoration, to provide detailed references for plant landscape design of China.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Sponsored by Humanities and Social Sciences Project of Basic Scientifi c Research Program of Northwest Agriculture&Forestry University(2014RWYB25)
文摘This paper elaborated the role of color composition in plant landscape design of Chicago Botanic Garden systematically, used examples to analyze color design of plant landscapes in the garden, and the specifi c application of color contrast in wall plant decoration, courtyard waterscape, indoor greenhouse and tree decoration, to provide detailed references for plant landscape design of China.
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。
