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Chen Yong
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Real-time Colorized Video Images Optimization Method in Scotopic Vision Chen Yong; Shuai Feng; Zhan Di
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 2: August 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i2.pp321-330

Abstract

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.
Image Mosaic Method Based on Gaussian Second-order Difference Feature Operator Chen Yong; Hao Yu-bin Hao; Zhan Di
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 2: August 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i2.pp336-345

Abstract

To compose the wide visual angle and high resolution image from the sequence of images which have overlapping region in the same scene quickly and correctly, an improved SIFT algorithm which is based on D2oG interest point detector was proposed. It extracted the image feature points and generated corresponding feature descriptors by improved SIFT algorithm. Then, using the random consistency (RANSAC) algorithm purified feature point matching pairs and calculating the transformation matrix H. Last, complete the seamless mosaic of images by using the image fusion algorithm of slipping into and out. It respectively process the images which had the four typical transformations with the traditional SIFT and the proposed method. The result indicated that the number of feature pairs is fewer than SIFT algorithm and the mosaic time is shorter, and then the matching efficiency is higher than the later. This proposed method reduces the complexity of operation and improves real-time of image mosaic simultaneously.
Co-Authors Hao Yu-bin Hao Shuai Feng Zhan Di