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针对关键视觉任务进行图像增强个性化：利用色彩处理和视觉错觉提高纸莎草纸文稿的易读性。

Personalizing image enhancement for critical visual tasks: improved legibility of papyri using color processing and visual illusions.

作者信息

Atanasiu Vlad, Marthot-Santaniello Isabelle

机构信息

Department of Informatics, University of Fribourg, Fribourg, Switzerland.

Department of Ancient Studies, University of Basel, Basel, Switzerland.

出版信息

Int J Doc Anal Recognit. 2022;25(2):129-160. doi: 10.1007/s10032-021-00386-0. Epub 2021 Dec 27.

DOI:10.1007/s10032-021-00386-0
PMID:35582702
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9106648/
Abstract

UNLABELLED

This article develops theoretical, algorithmic, perceptual, and interaction aspects of script legibility enhancement in the visible light spectrum for the purpose of scholarly editing of papyri texts. Novel legibility enhancement algorithms based on color processing and visual illusions are compared to classic methods in a user experience experiment. (1) The proposed methods outperformed the comparison methods. (2) Users exhibited a broad behavioral spectrum, under the influence of factors such as personality and social conditioning, tasks and application domains, expertise level and image quality, and affordances of software, hardware, and interfaces. No single enhancement method satisfied all factor configurations. Therefore, it is suggested to offer users a broad choice of methods to facilitate personalization, contextualization, and complementarity. (3) A distinction is made between casual and critical vision on the basis of signal ambiguity and error consequences. The criteria of a paradigm for enhancing images for critical applications comprise: interpreting images skeptically; approaching enhancement as a system problem; considering all image structures as potential information; and making uncertainty and alternative interpretations explicit, both visually and numerically.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10032-021-00386-0.

摘要

未标注

本文针对纸莎草纸文本的学术编辑，从理论、算法、感知和交互等方面探讨了可见光光谱中文字易读性增强的问题。在一项用户体验实验中，将基于颜色处理和视觉错觉的新型易读性增强算法与经典方法进行了比较。（1）所提出的方法优于比较方法。（2）在个性和社会条件、任务和应用领域、专业水平和图像质量以及软件、硬件和界面的可用性等因素的影响下，用户表现出广泛的行为范围。没有一种单一的增强方法能满足所有因素配置。因此，建议为用户提供广泛的方法选择，以促进个性化、情境化和互补性。（3）根据信号模糊性和错误后果，区分了随意视觉和批判性视觉。用于关键应用的图像增强范式的标准包括：以怀疑的态度解释图像；将增强视为一个系统问题；将所有图像结构视为潜在信息；并在视觉和数值上明确不确定性和替代解释。

补充信息

在线版本包含可在10.1007/s10032-021-00386-0获取的补充材料。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c16/9106648/5d2702f07f0d/10032_2021_386_Fig18_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c16/9106648/2473cccd8a15/10032_2021_386_Fig12_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c16/9106648/034266fadd8c/10032_2021_386_Fig17_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c16/9106648/2473cccd8a15/10032_2021_386_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c16/9106648/fd12e6e0b89f/10032_2021_386_Fig13_HTML.jpg
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