一种新的白天户外图像的内在照明色彩空间

IF 10.8 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE IEEE Transactions on Image Processing Pub Date : 2017-02-01 DOI:10.1109/TIP.2016.2642788
Zhi Han, Jiandong Tian, Liangqiong Qu, Yandong Tang
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引用次数: 6

摘要

从自然图像中提取或分离内在信息和光照对于更好地解决计算机视觉任务至关重要。在本文中,我们提出了一种新的基于照度的色彩空间,即IL (intrinsic information and lighting level)空间。它的前两个通道表示2D固有信息,第三个通道表示照明水平。IL色彩空间与RGB色彩空间具有一对一的对应关系。IL色彩空间的一个有价值的好处是,与照明相关的处理可以通过直接在照明通道上操作来实现。以提取的光照通道为例,提出了一种新的算法来估计图像的内在光照水平,从而获得无阴影彩色图像和重光照序列。与现有的用于显示或打印的色彩空间相比,IL色彩空间直观地分别显示颜色的反射率和照明等级信息
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A New Intrinsic-Lighting Color Space for Daytime Outdoor Images
Extracting or separating intrinsic information and illumination from natural images is crucial for better solving computer vision tasks. In this paper, we present a new illumination-based color space, the IL (intrinsic information and lighting level) space. Its first two channels represent 2D intrinsic information, and the third channel is for lighting levels. The IL color space has a one-to-one correspondence with the RGB color space. One valuable benefit of the IL color space is that illumination-related processing can be realized by directly operating on the lighting channel. As an example, based on the extracted lighting channel, we propose a new algorithm to estimate the intrinsic lighting level of an image such that the shadow-free color image and relighting series are obtained. In contrast to the existing color spaces for display or printing, the IL color space intuitively shows the information of reflectance and lighting levels for colors separately
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来源期刊
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing 工程技术-工程:电子与电气
CiteScore
20.90
自引率
6.60%
发文量
774
审稿时长
7.6 months
期刊介绍: The IEEE Transactions on Image Processing delves into groundbreaking theories, algorithms, and structures concerning the generation, acquisition, manipulation, transmission, scrutiny, and presentation of images, video, and multidimensional signals across diverse applications. Topics span mathematical, statistical, and perceptual aspects, encompassing modeling, representation, formation, coding, filtering, enhancement, restoration, rendering, halftoning, search, and analysis of images, video, and multidimensional signals. Pertinent applications range from image and video communications to electronic imaging, biomedical imaging, image and video systems, and remote sensing.
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