Long-Distance Object Recognition With Image Super Resolution: A Comparative Study | Zendy

Xiaomin Yang | Zendy; Wei Wu | Zendy; Kai Liu | Zendy; Pyoung Won Kim | Zendy; Arun Kumar Sangaiah | Zendy; Gwanggil Jeon | Zendy

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Long-Distance Object Recognition With Image Super Resolution: A Comparative Study

Author(s) -

Xiaomin Yang,

Wei Wu,

Kai Liu,

Pyoung Won Kim,

Arun Kumar Sangaiah,

Gwanggil Jeon

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2799861

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

Monitor systems are ubiquitously deployed in public areas. However, monitor systems face a major challenge regarding long-distance object recognition. Super-resolution constitutes a popular choice to address this challenge. Since super-resolution methods are used in many applications, it is necessary to understand these methods and make a comparative study of them. In this paper, we perform a comparative study on six super-resolution methods over two recognition algorithms. The paper evaluates super-resolution performance based on recognition accuracy, and serves as a summary assessment of image super-resolution algorithms.

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