Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/102624
Title: 基于Contourlet统计特性的无参考图像质量评价 = No-reference quality assessment based on the statistics in Cntourlet domain
Authors: 焦淑红 Jiao Shu-hong
齐欢 Qi Huan
林维斯 Lin Wei-si
唐琳 Tang Lin
申维和 Shen Wei-he
Keywords: DRNTU::Engineering::Computer science and engineering
图像质量评价
信息处理技术
Issue Date: 2016
Source: Jiao, S., Qi, H., Lin, W., Tang, L., & Shen, W. (2016). 基于Contourlet统计特性的无参考图像质量评价 = No-reference quality assessment based on the statistics in Cntourlet domain. 吉林大学学报(工学版) Journal of Jilin University (Engineering and Technology Edition), 46(2), 639-645. doi:10.13229/j.cnki.jdxbgxb201602045
Series/Report no.: 吉林大学学报(工学版) Journal of Jilin University (Engineering and Technology Edition)
Abstract: 利用Contourlet统计特征建立自然统计模型与待评价图像模型,提出了Contourlet域无参考图像质量评价方法(SCIQA)。通过在主观数据库上的实验表明,无论同种干扰类型的图像还是多种干扰图像集合,SCIQA均明显优于经典全参考算法和通用型无参考算法,并且具有较强的通用性。 The statistic features in Cntourlet domain are employed to build the natural statistic model and the tested image model first. Then a no-reference assessment algorithm in Coutourlet domain (SCIQR) is proposed. Experiment results on subjective databases show that SCIQR outperforms the classical full-reference image quality assessment algorithm and the universal no-reference algorithm nomatter on single distortion type images and on the set of different types of distortion images. The demonstrates that SCIQR has good universality.
URI: https://hdl.handle.net/10356/102624
http://hdl.handle.net/10220/47268
URL: http://xuebao.jlu.edu.cn/gxb
ISSN: 1671-5497
DOI: 10.13229/j.cnki.jdxbgxb201602045
Rights: © 2016 吉林大学学报(工学版)编辑部. This paper was published in 吉林大学学报(工学版) Journal of Jilin University (Engineering and Technology Edition) and is made available as an electronic reprint (preprint) with permission of 吉林大学学报(工学版)编辑部. The published version is available at: [http://dx.doi.org/10.13229/j.cnki.jdxbgxb201602045]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.
Fulltext Permission: open
Fulltext Availability: With Fulltext
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