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1.中国科学院信息工程研究所信息安全国家重点实验室,北京 100093
2.之江实验室,浙江杭州 311100
3.中国科学院大学网络空间安全学院,北京 100049
Received:21 September 2021,
Revised:2021-11-17,
Published:25 August 2023
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王潇,尧思远,代朋纹等.基于阴影和周边区域色差的光照条件和光谱反射率计算方法[J].电子学报,2023,51(08):2098-2109.
WANG Xiao,YAO Si-yuan,DAI Peng-wen,et al.Estimating Illumination Condition and Spectral Reflectance Based on the Color Variation Between Shadowed Region and Its Surrounding Regions[J].ACTA ELECTRONICA SINICA,2023,51(08):2098-2109.
王潇,尧思远,代朋纹等.基于阴影和周边区域色差的光照条件和光谱反射率计算方法[J].电子学报,2023,51(08):2098-2109. DOI: 10.12263/DZXB.20211291.
WANG Xiao,YAO Si-yuan,DAI Peng-wen,et al.Estimating Illumination Condition and Spectral Reflectance Based on the Color Variation Between Shadowed Region and Its Surrounding Regions[J].ACTA ELECTRONICA SINICA,2023,51(08):2098-2109. DOI: 10.12263/DZXB.20211291.
光照条件和光谱反射率对增强现实和场景渲染任务非常有用,但是通过仪器采集比较困难,因此根据普通图像计算光照条件和光谱反射率是重要的计算机视觉任务.本文设计了一种通过分析场景中的阴影区域和周边区域颜色之间的色差,无需训练数据即可计算场景的光照条件和光谱反射率的算法.在自然场景中,阴影区域由于遮挡只能接收和反射天空光,而其周边的非阴影区域则同时受到太阳光和天空光的影响.当阴影和非阴影区域有着相同的光谱反射率时,两块区域颜色之间的色差反映了被遮挡光源的信息.两块区域之间的颜色差异由光照条件造成,又以光谱反射率为联系.因此,可以利用这两种颜色之间的关系计算光照条件和光谱反射率.本文使用先验知识和模型公式化表达某一区域在光照下呈现在图像中的颜色,然后基于两种颜色以及两者之间的色差设计了一种优化算法,通过计算最优解来计算场景的光照条件以及光谱反射率.通过在多个数据集上的一系列对比实验,以及一个使用光照条件和光谱反射率来去除阴影区域的应用实验,证明了该算法的准确性.
The illumination condition and the spectral reflectance are very useful for scene rendering and augmented reality but difficult to collect. Thus
it is an important task to get them from ordinary image. In this paper
we proposed a method that estimates illumination condition and spectral reflectance of natural scene without training process by analyzing the color variation between shadowed region and its surrounding regions. In natural scenes
the shadowed region was only lighted by skylight while its surrounding unshadowed regions were lighted by both sunlight and skylight. The color variation between them was the effect of shielded light source when they had the same spectral reflectance. The difference between these two colors was caused by the illumination condition of captured scene
while they were connected by their spectral reflectance. These colors provided the cue to calculate the illumination condition and the spectral reflectance. We formulized the whole process of image generation using prior knowledge and model. Then
we designed an optimization function based on the relationship between these colors to estimate the illumination condition and the spectral reflectance. The results of comparison experiment and the application experiment on shadow removal showed that the proposed method performed favorably against the state-of-the-art methods.
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