文章摘要
邵雪,曾台英,汪祖辉.基于亮度阈值效应的无参考图像质量评价方法[J].包装工程,2016,37(15):40-45.
SHAO Xue,ZENG Tai-ying,WANG Zu-hui.A Method for Quality Evaluation of No-reference Image Based on Luminance Threshold Effect[J].Packaging Engineering,2016,37(15):40-45.
基于亮度阈值效应的无参考图像质量评价方法
A Method for Quality Evaluation of No-reference Image Based on Luminance Threshold Effect
投稿时间:2015-11-10  修订日期:2016-08-10
DOI:
中文关键词: 无参考图像质量评价  亮度阈值  BRISQUE  主观评价
英文关键词: no-reference image quality evaluation  luminance threshold  BRISQUE  subjective evaluation
基金项目:新闻出版总署数字印刷工程研究中心数字传播重点实验室基金(10-00-309-000)
作者单位
邵雪 上海理工大学上海 200093 
曾台英 上海理工大学上海 200093 
汪祖辉 上海理工大学上海 200093 
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中文摘要:
      目的 图像质量的优劣不仅与失真有关,同时与亮度图像的质量有关,而无参考图像质量评价中未考虑到亮度图像的质量对图像整体质量评价的影响,因此引入亮度阈值效应对其亮度图像的质量进行量化评价。方法 在BRISQUE算法的基础上进行改进,以快速衰落失真为例,在调整亮度后获取的50幅图像库中进行实验,将失真图像分层为入射分量和反射分量,对入射分量(亮度图像)采用亮度阈值算法,反射分量(反射图像)采用BRISQUE算法,提出一种新的无参考图像质量评价方法。结果 文中算法的皮尔逊相关系数(PCC)为0.9982,斯皮尔曼秩相关系数(SROCC)为0.9741。结论 由实验数据可知,文中算法在人眼视觉的主观评价上相较于BRISQUE算法有更好的一致性,符合人眼的视觉感知。
英文摘要:
      Image quality is not only related to distortion, but also with the quality of the luminance image. No-reference image quality evaluation has not considered the impact of the quality of the luminance image on the image's whole quality. Therefore, the luminance threshold effect is introduced to quantify the evaluation of the image's luminance image. Based on the BRISQUE algorithm and with fast fading distortion as an example, experiments were carried out for the 50 images acquired by adjusting their background luminance. The distortion image was stratified into the incident and reflected components. Luminance threshold algorithm was adopted for the incident component (luminance image) and BRISQUE algorithm for the reflection component (reflect image). A new method for evaluating the quality of no reference image was put forward. The Pearson correlation coefficient (PCC) of the proposed algorithm was 0.9982, and the Spearman's Rank ordered Correlation Coefficient (SROCC) value was 0.9741. According to the experimental data, this algorithm has better consistency with the subjective evaluation of human vision than the BRISQUE algorithm and fits the human visual perception.
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