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Extraction of Artists' Color Features of Art Paintings and its Application to Color Image Correction

机译:艺术家彩色彩色特征的提取及其在彩色图像校正中的应用

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This paper proposes a method to extract artists' color features of art paintings, and correct the color-mismatch images of paintings based on artists' color features. First, we describe a standard image database consisting of famous oil paintings we captured directly, and an algorithm for extracting artists' color features based on the color distribution of the standard image data for each artist. The color distribution is analyzed by PCA and described with an ellipsoid to represent the standard color features for the artist. It is suggested that the color features for the respective artists are similar to the human visual assessment of their paintings. Next, the color correction is based on the coordinate transformation of pixel values in a color-mismatch image so that the color features of the mismatched image are fitted to the artist's color features in the standard image database. We present a correction algorithm using sRGB and CIELAB color spaces. Experiments are performed using samples of color-mismatch images of the famous oil paintings.
机译:本文提出了一种提取艺术家艺术绘画的彩色特征的方法,并根据艺术家的颜色特征来校正绘画的颜色不匹配图像。首先,我们描述了由我们直接捕获的着名石油绘画的标准图像数据库,以及基于每个艺术家的标准图像数据的颜色分布来提取艺术家颜色特征的算法。 PCA分析颜色分布,并用椭圆体描述,以表示艺术家的标准颜色特征。建议各艺术家的颜色特征类似于对其绘画的人类视觉评估。接下来,颜色校正基于颜色不匹配图像中的像素值的坐标变换,使得不匹配图像的颜色特征适用于标准图像数据库中的艺术家的颜色特征。我们使用SRGB和Cielab颜色空间呈现校正算法。使用着名油画的颜色不匹配图像的样本进行实验。

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