Detecting and Removing Specular Reflectance Components Based on Image Linearization
Author(s) -
Ryosuke Nakao,
Yuji Iwahori,
Yoshinori Adachi,
Aili Wang,
M. K. Bhuyan,
Boonserm Kijsirikul
Publication year - 2019
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2019.09.328
Subject(s) - specular reflection , computer science , reflectivity , diffuse reflection , photometric stereo , linearization , computer vision , bidirectional reflectance distribution function , specular highlight , artificial intelligence , reflection (computer programming) , image (mathematics) , optics , physics , nonlinear system , quantum mechanics , programming language
Shape from Shading and Photometric Stereo are famous approaches to recover the 3D shape from image(s). These approaches can obtain 3D shape from observed gray scale image(s) but it is necessary to estimate reflectance parameters for objects when some specular reflectance components are observed. Specular reflectance is difficult to be handled as diffuse reflectance in general. It is expected to remove specular reflectance component without assuming any kind of reflectance function (reflectance model). This paper proposes a method to remove specular reflection components using 4 observed images taken under 4 different light source directions using relighting approach of diffused reflectance based on image linearization. Results are demonstrated via computer simulation and experiments.
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