中山大学学报（自然科学版）Issue(6)：165-170,6.
基于小波高频奇异值分解的无参考模糊图像质量评价
A No-reference Blur Image Quality Assessment Algorithm Based on Wavelet High Frequency Singular Value Decomposition
摘要
Abstract
Traditional no reference blur image quality assessment methods usually need a pre-training and learning or a reference image constructing procedure,this result in the algorithm with high computa-tion cost.Aiming to this,a simple and effective no reference blur image quality assessment algorithm is proposed based on wavelet high frequency coefficients singular value decomposition.The method is build on the observations that the different wavelet high frequency sub-bands in the same scale of an image are highly structural correlation,and the degree of correlation would be reduced as the blur distortion deepe-ning.According to this,the new method first makes wavelet transform to the image,then makes singular value decomposition to the high frequency sub-bands to get their structure information.Finally,the an-gles,which represents the similarity,between different high frequency sub-bands’structural vectors are calculated and the sum of angles is used as the last objective assessment index.Experiments results show its good effectiveness and performance on LIVE2,CSIQ and TID2013databases and compared to the tra-ditional no-reference methods,the proposed algorithm is more efficient and practical as it does not need to train or create a reference image.关键词
无参考图像质量评价/小波变换/模糊图像/奇异值分解Key words
no-reference image quality assessment/wavelet transform/blur Image/singular value de-composition分类
信息技术与安全科学引用本文复制引用
黄晓生,严浩,曹义亲,李亚琴..基于小波高频奇异值分解的无参考模糊图像质量评价[J].中山大学学报（自然科学版）,2014,(6):165-170,6.基金项目
国家自然科学基金资助项目（61365008）；江西省自然科学基金资助项目 （）
