Real-time Colorized Video Images Optimization Method in Scotopic Vision
Author(s) -
Yong Chen,
Shuai Feng,
Zhan Di
Publication year - 2015
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v15.i2.pp321-330
Subject(s) - computer vision , artificial intelligence , computer science , contrast (vision) , brightness , pixel , compensation (psychology) , video processing , human visual system model , image resolution , feature (linguistics) , image (mathematics) , optics , physics , philosophy , psychology , psychoanalysis , linguistics
In low light environment, the surveillance video image has lower contrast less information and uneven brightness. To solve this problem, this paper puts forward a contrast resolution compensation algorithm based on human visual perception model. It extracts Y component from the YUV video image acquired by camera originally to subtract contrast feature parameters, then makes a proportional integral type contrast resolution compensation for low light pixels in Y component and makes index contrast resolution compensation for high light pixels adaptively to enhance brightness of the video image while maintains the U and V components. Then it compresses the video images and transmits them via internet. Finally, it decodes and displays the video image on the device of intelligent surveillance system. The experimental results show that, the algorithm can effectively improve the contrast resolution of the video image and maintain the color of video image well. It also can meet the real-time requirement of video monitoring.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom