Modeling a Low Vision Observer: Application in Comparison of Image Enhancement Methods - Archive ouverte HAL Accéder directement au contenu
Chapitre D'ouvrage Année : 2020

Modeling a Low Vision Observer: Application in Comparison of Image Enhancement Methods

(1) , (1) , (1)
1

Résumé

Numerous image processing methods have been proposed to help low vision people, often relied on contrast enhancement algorithms. Their assessment is usually performed by tests on low vision subjects, which are expensive and time consuming. This paper presents a low vision observer model, fully customizable to fit various impaired visual performances, which may be used for early algorithm assessment, and avoiding unnecessary human tests. This model is fitted to visual performances of a subject with degenerative retinal disease, and applied to images processed by two edge enhancement algorithms, allowing to explain their performances in terms of blur reduction and color saturation improvement.
Fichier non déposé

Dates et versions

hal-03066189 , version 1 (15-12-2020)

Identifiants

Citer

Cédric Walbrecq, Dominique Lafon-Pham, Isabelle Marc. Modeling a Low Vision Observer: Application in Comparison of Image Enhancement Methods. HCI International 2020 – Late Breaking Posters, pp.119-126, 2020, 978-3-030-60703-6. ⟨10.1007/978-3-030-60703-6_15⟩. ⟨hal-03066189⟩
56 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook Twitter LinkedIn More