Open AccessEdge detection based on gradient ghost imaging
Author(s) -
Xuefeng Liu,
XuRi Yao,
RuoMing Lan,
Chao Wang,
Guangtao Zhai
Publication year - 2015
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.23.033802
Subject(s) - ghost imaging , edge detection , morphological gradient , enhanced data rates for gsm evolution , computer science , optics , artificial intelligence , computer vision , physics , image gradient , object detection , image processing , image (mathematics) , segmentation
We present an experimental demonstration of edge detection based on ghost imaging (GI) in the gradient domain. Through modification of a random light field, gradient GI (GGI) can directly give the edge of an object without needing the original image. As edges of real objects are usually sparser than the original objects, the signal-to-noise ratio (SNR) of the edge detection result will be dramatically enhanced, especially for large-area, high-transmittance objects. In this study, we experimentally perform one- and two-dimensional edge detection with a double-slit based on GI and GGI. The use of GGI improves the SNR significantly in both cases. Gray-scale objects are also studied by the use of simulation. The special advantages of GI will make the edge detection based on GGI be valuable in real applications.