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RISS 인기검색어
- 검색키워드
- 저자 : Zhengyou Wang (검색결과 3 건)
- 무료
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- 유료
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A New Image Quality Assessment Algorithm based on SSIM and Multiple Regressions
Zhengyou Wang,Liying Li,Shuang Wu,Yanhui Xia,Zheng Wan,Cong Cai 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.11
Image quality assessment (IQA) is crucial in image processing algorithms. In the state-of-the-art IQA index, the structural similarity (SSIM) index has been proved to be better objective quality assessment metric. However, the accuracy of SSIM is relatively lacking when used to access blurred images. And the component weights of structural similarity (SSIM) index are fixed in some past environments. So an improved assessment algorithm incorporating multiple linear regressions and SSIM index was proposed in this paper. We use regression analysis to adjust the component weight of SSIM index. So the improved algorithm is more accuracy on different distortion types’ quality assessment. Experimental results show that the improved SSIM algorithm is better than traditional methods in nonlinear regression correlation coefficient, Spearman correlation coefficient and out ratio.
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Web-Based Collaborative Learning System and Its Key Techniques
Yanhui Xia,Zhengyou Wang,Yi Li,Jinfeng Hu 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.12
On the basis of concept, characteristics and related work of collaborative learning, this paper proposes an intelligent web collaborative learning system prototype based on multi-agent technology. At first, the paper introduces a collaborative learning framework which supporting group learning and illustrates the whole learning process. Secondly, the paper presents some key issues to implementation of the virtual learning environment, such as intelligent grouping, automatic question answering, knowledge management, and opinion mining. Preliminary learning practice shows that it is a practical and efficient way.
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An Improved H.264 Encoded Algorithm Based on Weber-Fechner Law
Yanhui Xia,Baisheng Nie,Zhengyou Wang,Liying Li,Jianhua Ming,Zheng Wan,Shuying Huang 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.9
With the study of human visual system (HVS), people find that the human eye shows different degree of sensitivity to different light signals. A higher background brightness region of the human eye for the distortion, the degree of sensitivity will be greatly reduced. The human eye’s sensitivity will be greatly reduced to the distortion of a higher brightness background region. This finding is discribed in Weber-Fechner law. Therefore, the encoder can be improved by employing this characteristic of human visual system. In this paper, the authors use this characteristic to improve the H.264 video coding algorithm. In order to improve the compression efficiency of encoder, give the brightness of different regions with different levels of quantification by adjusting the quantization step size (QP), without affecting the subjective quality of video. Experimental results show that the output bit rate decrease up to 10% -20% by using this improved algorithm in H.264 reference encoder, and the subjective quality of decoded image by using this improved algorithm is as good as the standard H.264 encoders.
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