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

• URL: http://arxiv.org/abs/2104.01106v2
• Date: Mon, 30 Aug 2021 21:28:00 GMT
• Title: Personalizing image enhancement for critical visual tasks: improved legibility of papyri using color processing and visual illusions
• Authors: Vlad Atanasiu, Isabelle Marthot-Santaniello
• Abstract summary: Methods: Novel enhancement algorithms based on color processing and visual illusions are compared to classic methods in a user experience experiment. 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.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Purpose: 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. - Methods: Novel legibility enhancement algorithms based on color processing and visual illusions are compared to classic methods in a user experience experiment. - Results: (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.

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