Pixel-wise Orthogonal Decomposition for Color Illumination Invariant and Shadow-free Image

Pixel-wise Orthogonal Decomposition for Color Illumination Invariant and Shadow-free Image
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彩色照明不变无影图像的逐像素正交分解

DOI:
10.1364/oe.23.002220
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发表时间:
2014-06
期刊:
影响因子:
3.8
通讯作者:
唐延东
唐延东
中科院分区:
物理与天体物理2区
文献类型:
--
作者:
屈靓琼;田建东;韩志;唐延东

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本文提出了一种新颖、有效、快速的从单幅室外图像中获取彩色光照不变、无阴影图像的方法。与现有的无阴影图像处理方法需要阴影检测或统计学习不同,我们基于物理阴影不变量为每个像素值向量建立线性方程组,并推导出其解的逐个像素点正交分解,进而得到图像上每个像素值向量的光照不变量向量。光照不变向量是线性方程组的唯一特解,它与其自由解是正交的。利用该光照不变向量和Lab颜色空间,我们提出了一种能够很好地保留原始图像的纹理和颜色信息的无阴影图像生成算法。在一组不同的室外图像上进行了一系列实验,并与最先进的方法进行了比较,验证了我们的方法。
In this paper, we propose a novel, effective and fast method to obtain a color illumination invariant and shadow-free image from a single outdoor image. Different from state-of-the-art methods for shadow-free image that either need shadow detection or statistical learning, we set up a linear equation set for each pixel value vector based on physically-based shadow invariants, deduce a pixel-wise orthogonal decomposition for its solutions, and then get an illumination invariant vector for each pixel value vector on an image. The illumination invariant vector is the unique particular solution of the linear equation set, which is orthogonal to its free solutions. With this illumination invariant vector and Lab color space, we propose an algorithm to generate a shadow-free image which well preserves the texture and color information of the original image. A series of experiments on a diverse set of outdoor images and the comparisons with the state-of-the-art methods validate our method.
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