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基于图像融合的无参考立体图像质量评价

No-Reference Stereo Image Quality Assessment Based on Image Fusion

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摘要

提出了一种基于图像融合的无参考立体图像质量评价算法。该算法利用小波变换分解重构立体图像的左右视图并融合在一幅图像中,归一化处理融合图像的亮度系数,均衡各部分亮度并保留融合图像的结构信息,使用卷积神经网络进行特征提取和回归预测。实验结果表明,所提方法的预测得分与人类主观评价得分具有很好的一致性。

Abstract

A no-reference stereo image quality assessment algorithm based on image fusion is proposed. The algorithm reconstructs the left and right views of the stereo image by wavelet transform and fuses them into one image. The luminance coefficient of the fused image is normalized, which keeps the brightness of each part in balance and preserves the structural information of the fused image. Finally the convolutional neural network is used to extract feature and predict regression. The experimental results show that the predicted scores of the proposed method are in good agreement with the human subjective assessment scores.

Newport宣传-MKS新实验室计划
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中图分类号:TP391.41

DOI:10.3788/lop56.071004

所属栏目:图像处理

基金项目:江苏省自然科学基金(BK20171142)

收稿日期:2018-09-18

修改稿日期:2018-09-30

网络出版日期:2018-10-25

作者单位    点击查看

黄姝钰:江南大学物联网工程学院江苏省模式识别与计算智能工程实验室, 江苏 无锡 214122
桑庆兵:江南大学物联网工程学院江苏省模式识别与计算智能工程实验室, 江苏 无锡 214122

联系人作者:桑庆兵(sangqb@163.com)

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引用该论文

Huang Shuyu,Sang Qingbing. No-Reference Stereo Image Quality Assessment Based on Image Fusion[J]. Laser & Optoelectronics Progress, 2019, 56(7): 071004

黄姝钰,桑庆兵. 基于图像融合的无参考立体图像质量评价[J]. 激光与光电子学进展, 2019, 56(7): 071004

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