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空域特征结合小波域特征的图像多失真质量评价

Image Quality Assessment for Various Distortions Based on Spatial and Wavelet Domain Features
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摘要 为了解决受到多种降质因素影响的图像质量评价问题,提出了一种结合空间域和小波域特征提取的图像质量评价方法。根据图像的失真会影响图像数据在空间域和小波域的自然场景统计特性,并且失真程度可参数化的特点,计算空间域和小波域的高斯概率密度函数的主要参数并以此作为特征值来表征失真程度,然后将这些特征值作为支持向量回归的输入,训练并预测得到图像的质量得分。对LIVE2数据库的失真图像评价实验结果表明:该方法计算时间短,且预测得分和主观得分具有较好的一致性。 An image quality assessment method using features in spatial and wavelet domain is proposed,to assess the quality of multi-distorted images.According to the fact that not only distortions affect natural scene statistic,but also can be parameterized,this paper calculates the main parameters of Gaussian Probability Density function in spatial domain and wavelet domain as features indicating the degree of distortions.
出处 《工业控制计算机》 2017年第1期84-86,共3页 Industrial Control Computer
基金 浙江省自然科学基金重点资助项目(LZ14F030004) 国家自然科学基金资助项目(61571170) 上海航天科技创新基金(SAST2015041)资助
关键词 空间域 小波域 高斯概率密度函数 支持向量回归 spatial domain wavelet domain gaussian probability density function support vector regression
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