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在对立互补色彩系统中进行冷暖调节的脱色处理。

Decolorization with Warmth-Coolness Adjustment in an Opponent and Complementary Color System.

作者信息

Sanchez-Cesteros Oscar, Rincon Mariano

机构信息

Department of Artificial Intelligence, Universidad Nacional de Educación a Distancia (UNED), Juan del Rosal, 16, 28040 Madrid, Spain.

出版信息

J Imaging. 2025 Jun 18;11(6):199. doi: 10.3390/jimaging11060199.

DOI:10.3390/jimaging11060199
PMID:40558799
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12194648/
Abstract

Creating grayscale images from a color reality has been an inherent human practice since ancient times, but it became a technological challenge with the advent of the first black-and-white televisions and digital image processing. Decolorization is a process that projects visual information from a three-dimensional feature space to a one-dimensional space, thus reducing the dimensionality of the image while minimizing the loss of information. To achieve this, various strategies have been developed, including the application of color channel weights and the analysis of local and global image contrast, but there is no universal solution. In this paper, we propose a bio-inspired approach that combines findings from neuroscience on the architecture of the visual system and color coding with evidence from studies in the psychology of art. The goal is to simplify the decolorization process and facilitate its control through color-related concepts that are easily understandable to humans. This new method organizes colors in a scale that links activity on the retina with a system of opponent and complementary channels, thus allowing the adjustment of the perception of warmth and coolness in the image. The results show an improvement in chromatic contrast, especially in the warmth and coolness categories, as well as an enhanced ability to preserve subtle contrasts, outperforming other approaches in the Ishihara test used in color blindness detection. In addition, the method offers a computational advantage by reducing the process through direct pixel-level operation.

摘要

自古以来,从彩色现实中创建灰度图像就是人类的固有做法,但随着第一台黑白电视机和数字图像处理技术的出现,它成为了一项技术挑战。去色是一个将视觉信息从三维特征空间投影到一维空间的过程,从而在最小化信息损失的同时降低图像的维度。为了实现这一目标,人们开发了各种策略,包括应用颜色通道权重以及分析局部和全局图像对比度,但尚无通用解决方案。在本文中,我们提出了一种受生物启发的方法,该方法将神经科学关于视觉系统结构和颜色编码的研究结果与艺术心理学研究的证据相结合。目标是简化去色过程,并通过人类易于理解的与颜色相关的概念来促进对其的控制。这种新方法以一种将视网膜上的活动与对立和互补通道系统联系起来的尺度来组织颜色,从而可以调整图像中冷暖色调的感知。结果表明,在色盲检测中使用的石原测试中,该方法在色彩对比度方面有了改进,尤其是在冷暖色调类别中,同时保留细微对比度的能力也有所增强,优于其他方法。此外,该方法通过直接的像素级操作减少了处理过程,具有计算优势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/8ddc2c9d4c2d/jimaging-11-00199-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/41911739fc9c/jimaging-11-00199-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/d55eb4401def/jimaging-11-00199-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/7179a4969199/jimaging-11-00199-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/c4e0080ce765/jimaging-11-00199-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/28ed8c090bb2/jimaging-11-00199-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/aab4b56ef2cf/jimaging-11-00199-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/691aa07d35b0/jimaging-11-00199-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/a3292b8b27b1/jimaging-11-00199-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/2bcd4913f3e3/jimaging-11-00199-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/c7b5ac4b42cb/jimaging-11-00199-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/8ddc2c9d4c2d/jimaging-11-00199-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/41911739fc9c/jimaging-11-00199-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/d55eb4401def/jimaging-11-00199-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/86230185c448/jimaging-11-00199-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/95af7cd714c4/jimaging-11-00199-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/7179a4969199/jimaging-11-00199-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/c4e0080ce765/jimaging-11-00199-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/28ed8c090bb2/jimaging-11-00199-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/aab4b56ef2cf/jimaging-11-00199-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/691aa07d35b0/jimaging-11-00199-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/a3292b8b27b1/jimaging-11-00199-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/2bcd4913f3e3/jimaging-11-00199-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/c7b5ac4b42cb/jimaging-11-00199-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e05/12194648/8ddc2c9d4c2d/jimaging-11-00199-g013.jpg

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