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基于多核学习和四元数小波变换的无参考图像质量评价

No-reference multiply distorted images quality assessment based on multiple kernel learning and quaternion wavelet transform
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摘要 为了能够有效地对各种类型失真立体图像的质量进行评价,文章基于广义高斯分布统计特性,提出了一种利用四元数小波变换的通用型无参考立体图像质量评价算法,通过广义高斯函数来拟合小波系数分布,采用SSIM匹配算法获取立体图像的深度信息,并通过多核学习的方法,对失真立体图像的失真程度进行客观的评价,得到对应图像的客观评价值。 Based on the statistical characteristics of generalized Gaussian distribution,a general-purpose non-reference stereo image quality evaluation algorithm using quaternion wavelet transform is proposed to fit the wavelet coefficient distribution by generalized Gaussian function.The depth information of stereo image is obtained by SSIM matching algorithm.
作者 武利秀 姚晓峰 王松 高双 Wu Lixiu;Yao Xiaofeng;Wang Song;Gao Shuang(Jiangsu Key Construction Laboratory of IoT Application Technology,Taihu University of Wuxi,Wuxi 214000,China;Pactera Yuanhui Technology(Wuxi)Co.,Ltd.,Wuxi 214000,China)
机构地区 无锡太湖学院江苏省物联网应用技术重点建设实验室 文思海辉元辉科技(无锡)有限公司
出处 《无线互联科技》 2020年第11期119-121,共3页 Wireless Internet Technology
基金 国家重点研发项目(子课题),项目编号:2018YFD0400902。
关键词 无参考立体图像质量评价 四元数小波变换 多核学习 no-reference stereoscopic image quality assessment quaternion wavelet transform multiple kernel learning
分类号 TP391.41 [自动化与计算机技术—计算机应用技术]
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无线互联科技
2020年 第11期

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