TY - GEN
T1 - Performance Comparison of Typical Spatial Domain Image Enhancement for a Mobile Robot in Low Contrast Environment
AU - Zhang, Longzhi
AU - Wu, Dongmei
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/21
Y1 - 2018/12/21
N2 - Images could be understood and analyzed more easily through enhance processing. Generally, image enhancement can be divided into spatial domain enhancement and frequency domain enhancement according to different processing domains. Yet compared with frequency domain processing, spatial domain enhancement is more easily to realize real-time enhancement of images, namely, spatial domain processing is easier to satisfy the real-time requirements of applications in practical engineering. While, real-time is critical to robots for performing operations. Hence, this paper devotes to exploring performance of four typical spatial domain enhancement algorithms for a mobile robot operating in low contrast environment. More precisely, fundamental theory of contrast stretch, histogram equalization, histogram matching, and local histogram are overviewed. Furthermore, a mobile robot system is briefly introduced. Finally, in condition of low contrast, performance of above four algorithms are compared in mobile robot via experiments. This work will provide a basic reference for further research on image enhancement in robot vision.
AB - Images could be understood and analyzed more easily through enhance processing. Generally, image enhancement can be divided into spatial domain enhancement and frequency domain enhancement according to different processing domains. Yet compared with frequency domain processing, spatial domain enhancement is more easily to realize real-time enhancement of images, namely, spatial domain processing is easier to satisfy the real-time requirements of applications in practical engineering. While, real-time is critical to robots for performing operations. Hence, this paper devotes to exploring performance of four typical spatial domain enhancement algorithms for a mobile robot operating in low contrast environment. More precisely, fundamental theory of contrast stretch, histogram equalization, histogram matching, and local histogram are overviewed. Furthermore, a mobile robot system is briefly introduced. Finally, in condition of low contrast, performance of above four algorithms are compared in mobile robot via experiments. This work will provide a basic reference for further research on image enhancement in robot vision.
KW - image enhancement
KW - low contrast
KW - mobile robot
KW - performance
KW - spatial domaint enhancement
UR - https://www.scopus.com/pages/publications/85061060871
U2 - 10.1109/ICRAE.2018.8586702
DO - 10.1109/ICRAE.2018.8586702
M3 - 会议稿件
AN - SCOPUS:85061060871
T3 - 2018 3rd International Conference on Robotics and Automation Engineering, ICRAE 2018
SP - 87
EP - 91
BT - 2018 3rd International Conference on Robotics and Automation Engineering, ICRAE 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 3rd International Conference on Robotics and Automation Engineering, ICRAE 2018
Y2 - 17 November 2018 through 19 November 2018
ER -