Applying Quaternions to Recognize Hidden Details in Images: Rothko as a Case Study

IF 1.9 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Adam Aharony, Ron Hindi, Maor Valdman, Shai Gul
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Abstract

Images or paintings with homogeneous colors may appear dull to the naked eye; however, there may be numerous details in the image that are expressed through subtle changes in color. This manuscript introduces a novel approach that can uncover these concealed details via a transformation that increases the distance between adjacent pixels, ultimately leading to a newly modified version of the input image. We chose the artworks of Mark Rothko—famous for their simplicity and limited color palette—as a case study. Our approach offers a different perspective, leading to the discovery of either accidental or deliberate clusters of colors. Our method is based on the quaternion ring, wherein a suitable multiplication can be used to boost the color difference between neighboring pixels, thereby unveiling new details in the image. The quality of the transformation between the original image and the resultant versions can be measured by the ratio between the number of connected components in the original image (m) and the number of connected components in the output versions (n), which usually satisfies nm≫1. Although this procedure has been employed as a case study for artworks, it can be applied to any type of image with a similar simplicity and limited color palette.
应用四元数识别图像中的隐藏细节——以Rothko为例
颜色均匀的图像或绘画在肉眼看来可能显得暗淡;然而,图像中可能有许多细节是通过颜色的细微变化来表达的。这篇手稿介绍了一种新的方法,可以通过增加相邻像素之间距离的变换来揭示这些隐藏的细节,最终产生新的输入图像修改版本。我们选择了马克·罗斯科(Mark Rothko)的作品作为案例研究。罗斯科以其简洁和有限的调色板而闻名。我们的方法提供了一个不同的视角,导致偶然或故意发现颜色集群。我们的方法基于四元数环,其中可以使用适当的乘法来提高相邻像素之间的色差,从而揭示图像中的新细节。原始图像和结果版本之间的转换质量可以通过原始图像中连接分量的数量(m)和输出版本中连接分量数量(n)之间的比率来测量,该比率通常满足nḿ1。尽管该程序已被用作艺术品的案例研究,但它可以应用于任何类型的图像,具有类似的简单性和有限的调色板。
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来源期刊
Mathematical & Computational Applications
Mathematical & Computational Applications MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-
自引率
10.50%
发文量
86
审稿时长
12 weeks
期刊介绍: Mathematical and Computational Applications (MCA) is devoted to original research in the field of engineering, natural sciences or social sciences where mathematical and/or computational techniques are necessary for solving specific problems. The aim of the journal is to provide a medium by which a wide range of experience can be exchanged among researchers from diverse fields such as engineering (electrical, mechanical, civil, industrial, aeronautical, nuclear etc.), natural sciences (physics, mathematics, chemistry, biology etc.) or social sciences (administrative sciences, economics, political sciences etc.). The papers may be theoretical where mathematics is used in a nontrivial way or computational or combination of both. Each paper submitted will be reviewed and only papers of highest quality that contain original ideas and research will be published. Papers containing only experimental techniques and abstract mathematics without any sign of application are discouraged.
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