计算机技术与发展Issue(7)：86-90,5.DOI:10.3969/j.issn.1673-629X.2015.07.019
基于Curvelet变换的无参考图像质量评价
No-reference Image Quality Assessment Based on Curvelet Transform
摘要
Abstract
In order to effectively measure the quality of different types of image distortion,propose a no-reference image quality assess-ment method based on Curvelet transform and neural network,called CurveletIQA. First,get Curvelet coefficient by Curvelet transform for the distorted image,the Curvelet coefficient by asymmetric generalized Gaussian fitting,and finding the energy eigenvalue of wave direc-tion information,get a set of characteristic value. Simultaneously,have a cuckoo search algorithm to optimize the BP neural network and use the method of combination of the optimized neural network and Curvelet domain to predict the distorted image without reference. The resultant feature values into the neural network is trained to establish the nonlinear mapping relationship between statistics and subjective evaluation values. Then use the mapping relationship to obtain the predicted value of the input image. The LIVE database is verified. The experimental results show that compared with the current method of relevant literature,the algorithm can effectively evaluate a variety of distortion types,with higher consistency and accuracy.关键词
无参考图像质量评价/曲波变换/自然图像/非对称广义高斯分布Key words
no-reference image quality assessment/Curvelet transform/natural images/asymmetric generalized Gaussian distribution分类
信息技术与安全科学引用本文复制引用
周姣姣,吴亚东..基于Curvelet变换的无参考图像质量评价[J].计算机技术与发展,2015,(7):86-90,5.基金项目
四川省教育科研重点项目(13ZA0169) （13ZA0169）
核废物与环境安全国防重点学科实验室项目(13zxnk12) （13zxnk12）
