A Neural Network Processing Method Based on Self-Assembly Equipment for Optical Image Display Standardization

Zilong Liu; Yiqin Jiang; Yuxiao Li; Jin Li; Zhuoran Li; Shuguo Zhang; Yusheng Lian; Ruping Liu

doi:10.1109/ACCESS.2019.2942215

IEEE Access (Jan 2019)

A Neural Network Processing Method Based on Self-Assembly Equipment for Optical Image Display Standardization

Zilong Liu,
Yiqin Jiang,
Yuxiao Li,
Jin Li,
Zhuoran Li,
Shuguo Zhang,
Yusheng Lian,
Ruping Liu

Affiliations

Zilong Liu: ORCiD; Optic Division, National Institute of Metrology, Beijing, China
Yiqin Jiang: Optic Division, National Institute of Metrology, Beijing, China
Yuxiao Li: Optic Division, National Institute of Metrology, Beijing, China
Jin Li: Department of Engineering, Photonics and Sensors Group, University of Cambridge, Cambridge, U.K.
Zhuoran Li: Optic Division, National Institute of Metrology, Beijing, China
Shuguo Zhang: State Grid Beijing Electric Power Company Training Center, Beijing, China
Yusheng Lian: School of Printing and Packaging Engineering, Beijing Institute of Graphic Communication, Beijing, China
Ruping Liu: School of Printing and Packaging Engineering, Beijing Institute of Graphic Communication, Beijing, China

DOI: https://doi.org/10.1109/ACCESS.2019.2942215
Journal volume & issue: Vol. 7
pp. 137552 – 137559

Abstract

Read online

Optical image is a kind of important data for communication because it is a two or three -dimensions data set to express communication information such as geographical signal, medical signal, remote sensing signal, etc. Thus, how to express the optical image properly is critical for the communication analytics. A new display method for optical image is described which is derived from the concept-Grayscale Standard Display Function (GSDF) which has been defined in DICOM, a medical image standard. The method analysis GSDF based on neural network processing which is different to DICOM. And the training data are from a self-assembly Equipment in NIM which is a traceable optical display equipment. Thus, the method has common usage for all optical image display, exceeding medical image. Furthermore, it is suitable for standardization because of the traceability.

Optical image display Grayscale Standard Display Function (GSDF) neural network standardization

Published in IEEE Access

ISSN: 2169-3536 (Online)
Publisher: IEEE
Country of publisher: United States
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering
Website: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639

About the journal

Abstract

Keywords