Geometry of color perception. Part 1: structures and metrics of a homogeneous color space.

IF 2.3 4区 医学 Q1 Neuroscience
Edoardo Provenzi
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引用次数: 25

Abstract

This is the first half of a two-part paper dealing with the geometry of color perception. Here we analyze in detail the seminal 1974 work by H.L. Resnikoff, who showed that there are only two possible geometric structures and Riemannian metrics on the perceived color space [Formula: see text] compatible with the set of Schrödinger's axioms completed with the hypothesis of homogeneity. We recast Resnikoff's model into a more modern colorimetric setting, provide a much simpler proof of the main result of the original paper, and motivate the need of psychophysical experiments to confute or confirm the linearity of background transformations, which act transitively on [Formula: see text]. Finally, we show that the Riemannian metrics singled out by Resnikoff through an axiom on invariance under background transformations are not compatible with the crispening effect, thus motivating the need of further research about perceptual color metrics.

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色彩感知的几何学。第1部分:均匀色彩空间的结构和度量。
这是一篇由两部分组成的论文的第一部分,该论文涉及颜色感知的几何。在这里,我们详细分析1974年由H.L. Resnikoff的开创性工作,他表明在感知颜色空间上只有两种可能的几何结构和黎曼度量(公式:见文本)与Schrödinger的公理集兼容,该公理集由同质性假设完成。我们将Resnikoff的模型重新塑造成一个更现代的色度设置,为原始论文的主要结果提供了一个更简单的证明,并激发了心理物理实验的需要,以反驳或证实背景变换的线性,背景变换对[公式:见文本]起传递作用。最后,我们证明了Resnikoff通过背景变换下的不变性公理挑选出的黎曼度量与脆化效果不兼容,从而激发了对感知颜色度量的进一步研究的必要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Mathematical Neuroscience
Journal of Mathematical Neuroscience Neuroscience-Neuroscience (miscellaneous)
自引率
0.00%
发文量
0
审稿时长
13 weeks
期刊介绍: The Journal of Mathematical Neuroscience (JMN) publishes research articles on the mathematical modeling and analysis of all areas of neuroscience, i.e., the study of the nervous system and its dysfunctions. The focus is on using mathematics as the primary tool for elucidating the fundamental mechanisms responsible for experimentally observed behaviours in neuroscience at all relevant scales, from the molecular world to that of cognition. The aim is to publish work that uses advanced mathematical techniques to illuminate these questions. It publishes full length original papers, rapid communications and review articles. Papers that combine theoretical results supported by convincing numerical experiments are especially encouraged. Papers that introduce and help develop those new pieces of mathematical theory which are likely to be relevant to future studies of the nervous system in general and the human brain in particular are also welcome.
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