Open AccessAdaptive compressed 3D ghost imaging based on the variation of surface normals
Author(s) -
Yan Qian,
Ruiqing He,
Qian Chen,
Guohua Gu,
Fanhuai Shi,
Wenwen Zhang
Publication year - 2019
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.27.027862
Subject(s) - ghost imaging , optics , pixel , surface reconstruction , surface (topology) , detector , computer science , computer vision , photometric stereo , stereo imaging , artificial intelligence , sampling (signal processing) , image quality , variation (astronomy) , physics , image (mathematics) , mathematics , geometry , astrophysics
Three-dimensional (3D) imaging can be reconstructed by a computational ghost imaging system with single pixel detectors based on a photometric stereo, but the requirement of large measurements and long imaging times are obstacles to its development. Also, the compressibility of the target's surface normals has not been fully studied, which causes the waste in sampling efficiency in single-pixel imaging. In this paper, we propose a method to adaptively measure the object's 3D information based on surface normals. In the proposed method, the regions of object's surface are illuminated by patterns of different spatial resolutions according to the variation of surface normals. The experimental results demonstrate that our proposed scheme can reduce measurements and preserve the quality of the formed 3D image.