Optimizing Tone Mapping Operators for Keypoint Detection under Illumination Changes

Abstract :

Tone mapping operators (TMO) have recently raised interest for their capability to handle illumination changes. However, these TMOs are optimized with respect to perception rather than image analysis tasks like keypoint detection. Moreover, no work has been done to analyze the factors affecting the optimization of TMOs for such tasks. In this paper, we investigate the influence of two factors– Correlation Coefficient (CC) and Repeatability Rate (RR) of the tone mapped images for the optimization of classical Retinex based models to enhance keypoint detection under illumination changes. CC-based optimized models aim at increasing the similarity of the tone mapped images. Conversely, RR-based optimized models quantify the optimal detection performance gains. By considering two simple Retinex based models, i.e., Gaussian and bilateral filtering, we show that estimating as precisely as possible the illumination, CC-based optimized models do not necessarily bring to optimal keypoint detection performance. We conclude that, instead, other criteria specific to RR-based optimized models should be taken into account. Moreover, large gains in performance with respect to existing popular TMOs motivate further research towards optimal tone mapping technique for computer vision applications.

Type de document :
Communication dans un congrès
2016 IEEE Workshop on Multimedia Signal Processing (MMSP 2016), Sep 2016, Montréal, Canada. 2016 IEEE Workshop on Multimedia Signal Processing (MMSP 2016), 2016, 〈http://mmsp2016.ece.mcgill.ca/default.html〉
Liste complète des métadonnées

Littérature citée [19 références]  Voir  Masquer  Télécharger

https://hal-imt.archives-ouvertes.fr/hal-01349708
Contributeur : Admin Télécom Paristech <>
Soumis le : jeudi 28 juillet 2016 - 13:58:08
Dernière modification le : jeudi 11 janvier 2018 - 06:23:39
Document(s) archivé(s) le : samedi 29 octobre 2016 - 10:50:13

Fichier

inproceedings-2016-16267-1.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01349708, version 1

Citation

Aakanksha Rana, Giuseppe Valenzise, Frederic Dufaux. Optimizing Tone Mapping Operators for Keypoint Detection under Illumination Changes. 2016 IEEE Workshop on Multimedia Signal Processing (MMSP 2016), Sep 2016, Montréal, Canada. 2016 IEEE Workshop on Multimedia Signal Processing (MMSP 2016), 2016, 〈http://mmsp2016.ece.mcgill.ca/default.html〉. 〈hal-01349708〉

Partager

Métriques

Consultations de la notice

324

Téléchargements de fichiers

140