Terahertz Security Image Quality Assessment by No-reference Model Observers
Menghan Hu, Xiongkuo Min, Guangtao Zhai, Wenhan Zhu, Yucheng Zhu,, Zhaodi Wang, Xiaokang Yang, Guang Tian

TL;DR
This paper evaluates no-reference image quality assessment algorithms for THz security images, finding that simple pixel intensity measures outperform complex models and proposing Fish_bb as a reliable substitute for subjective evaluation.
Contribution
It introduces a THz security image database and compares existing IQA algorithms, identifying the effectiveness of Fish_bb and pixel intensity for quality assessment.
Findings
Fish_bb outperforms other IQA algorithms with high correlation scores.
Average pixel intensity surpasses complex IQA models in accuracy.
S3 effectively classifies image quality with low false positive rate.
Abstract
To provide the possibility of developing objective image quality assessment (IQA) algorithms for THz security images, we constructed the THz security image database (THSID) including a total of 181 THz security images with the resolution of 127*380. The main distortion types in THz security images were first analyzed for the design of subjective evaluation criteria to acquire the mean opinion scores. Subsequently, the existing no-reference IQA algorithms, which were 5 opinion-aware approaches viz., NFERM, GMLF, DIIVINE, BRISQUE and BLIINDS2, and 8 opinion-unaware approaches viz., QAC, SISBLIM, NIQE, FISBLIM, CPBD, S3 and Fish_bb, were executed for the evaluation of the THz security image quality. The statistical results demonstrated the superiority of Fish_bb over the other testing IQA approaches for assessing the THz image quality with PLCC (SROCC) values of 0.8925 (-0.8706), and with…
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Taxonomy
TopicsImage and Video Quality Assessment · Advanced Data Compression Techniques · Terahertz technology and applications
