Specularity removal: a global energy minimization approach based on polarization imaging - Normandie Université Access content directly
Journal Articles Computer Vision and Image Understanding Year : 2017

Specularity removal: a global energy minimization approach based on polarization imaging

Abstract

Concentration of light energy in images causes strong highlights (specular reflection), and challenges the robustness of a large variety of vision algorithms, such as feature extraction and object detection. Many algorithms indeed assume perfect di↵use surfaces and ignore the specular reflections; specularity removal may thus be a preprocessing step to improve the accuracy of such algorithms. Regarding specularity removal, traditional color-based methods generate severe color distortions and local patch-based algorithms do not integrate long range information, which may result in artifacts. In this paper, we present a new image specularity removal method which is based on polarization imaging through global energy minimization. Polarization images provide complementary information and reduce color distortions. By minimizing a global energy function, our algorithm properly takes into account the long range cue and produces accurate and stable results. Compared to other polarization-based methods of the literature, our method obtains encouraging results, both in terms of accuracy and robustness.
Fichier principal
Vignette du fichier
specularity-removal-global-CVIU.pdf (942.95 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-02114528 , version 1 (29-04-2019)

Identifiers

Cite

Fan Wang, Samia Ainouz, Caroline Petitjean, Abdelaziz Bensrhair. Specularity removal: a global energy minimization approach based on polarization imaging. Computer Vision and Image Understanding, 2017, ⟨10.1016/j.cviu.2017.03.003⟩. ⟨hal-02114528⟩
68 View
631 Download

Altmetric

Share

Gmail Facebook X LinkedIn More