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A Wavelet-Predominant Algorithm Can Evaluate Quality of THz Security Image and Identify Its Usability
IEEE Transactions on Broadcasting ( IF 3.2 ) Pub Date : 2020-03-01 , DOI: 10.1109/tbc.2019.2901388
Menghan Hu , Guangtao Zhai , Rong Xie , Xiongkuo Min , Qingli Li , Xiaokang Yang , Wenjun Zhang

This paper presents an aggregate wavelet-predominant algorithm to measure the distortions in THz security images. The algorithm integrates a spectral-based sharpness estimator, a noise estimator derived alpha-stable model and an overall viewing experience estimator based on free-energy principle. Among them, the greater weight is assigned to the spectral-based sharpness estimator considering that the main quality factor in THz security image is sharpness. To verify the feasibility of the proposed metric, we construct the THz security image dataset including a total of 181 THz security images, and each image has the mean opinion score (MOS) collected via subjective quality evaluation experiment. Quantitative experimental results on the constructed THz security image dataset show that the aggregate wavelet-predominant estimator produces the promising overall performance for the estimation of MOS values, with PLCC, SROCC, and RMSE of 0.900, 0.873, and 0.386, respectively. This performance is superior to other opinion-unaware approaches, viz., FISBLIM, SISBLIM, NIQE, CPBD, SINE, S3, FISH, and noise estimator. The determination coefficient ( ${R} ^{{2}}$ ) of linear regression between reference and predicted MOSs is 0.81. The result of Bland–Altman analysis further validates that the aggregate wavelet-predominant estimator can substitute for the subjective IQA of THz security image, with approximately 94.5% of data points locating within the limits of agreement. For usability identification, the wavelet-predominant estimator gives the satisfactory results, with accuracy, precision, recall rate, and false positive rate of 84.0%, 79.8%, 95.0%, and 29.6%, respectively. Furthermore, the potential application perspectives of the proposed metric can refer to commercial applications (guarantee THz security images of good quality) and scientific researches (assist in software development for THz security image analysis). The dataset is available at https://doi.org/10.6084/m9.figshare.7700123.v3. Possible researches on this dataset may include the development of THz quality standards, the selection of the best display mode, the enhancement of images, the modeling of image noise, and the detection of prohibited goods.

中文翻译:

小波主导算法可以评估太赫兹安全图像的质量并确定其可用性

本文提出了一种聚合小波主导算法来测量太赫兹安全图像中的失真。该算法集成了基于频谱的锐度估计器、噪声估计器导出的 alpha 稳定模型和基于自由能原理的整体观看体验估计器。其中,考虑到太赫兹安全图像中的主要质量因素是锐度,更大的权重被分配给基于光谱的锐度估计器。为了验证所提出的度量的可行性,我们构建了包括总共 181 张 THz 安全图像的太赫兹安全图像数据集,每个图像都有通过主观质量评估实验收集的平均意见分数 (MOS)。对构建的太赫兹安全图像数据集的定量实验结果表明,聚合小波主导估计器对 MOS 值的估计产生了有希望的整体性能,PLCC、SROCC 和 RMSE 分别为 0.900、0.873 和 0.386。这种性能优于其他意见不感知方法,即 FISBLIM、SISBLIM、NIQE、CPBD、SINE、S3、FISH 和噪声估计器。参考和预测 MOS 之间线性回归的决定系数 ( ${R} ^{{2}}$ ) 为 0.81。Bland-Altman 分析的结果进一步验证了聚合小波主导估计器可以替代太赫兹安全图像的主观 IQA,大约 94.5% 的数据点位于一致性范围内。对于可用性识别,小波主导估计给出了令人满意的结果,准确率、准确率、召回率和误报率分别为 84.0%、79.8%、95.0% 和 29.6%。此外,所提出的度量的潜在应用前景可以参考商业应用(保证高质量的太赫兹安全图像)和科学研究(协助太赫兹安全图像分析的软件开发)。数据集可在 https://doi.org/10.6084/m9.figshare.7700123.v3 获得。对该数据集的可能研究可能包括太赫兹质量标准的制定、最佳显示模式的选择、图像的增强、图像噪声的建模以及违禁品的检测。此外,所提出的度量的潜在应用前景可以参考商业应用(保证高质量的太赫兹安全图像)和科学研究(协助太赫兹安全图像分析的软件开发)。数据集可在 https://doi.org/10.6084/m9.figshare.7700123.v3 获得。对该数据集的可能研究可能包括太赫兹质量标准的制定、最佳显示模式的选择、图像的增强、图像噪声的建模以及违禁品的检测。此外,所提出的度量的潜在应用前景可以参考商业应用(保证高质量的太赫兹安全图像)和科学研究(协助太赫兹安全图像分析的软件开发)。数据集可在 https://doi.org/10.6084/m9.figshare.7700123.v3 获得。对该数据集的可能研究可能包括太赫兹质量标准的制定、最佳显示模式的选择、图像的增强、图像噪声的建模以及违禁品的检测。figshare.7700123.v3。对该数据集的可能研究可能包括太赫兹质量标准的制定、最佳显示模式的选择、图像的增强、图像噪声的建模以及违禁品的检测。figshare.7700123.v3。对该数据集的可能研究可能包括太赫兹质量标准的制定、最佳显示模式的选择、图像的增强、图像噪声的建模以及违禁品的检测。
更新日期:2020-03-01
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