App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 7

No-reference hyperspectral image quality assessment with weakly-supervised and bidirectional spatial-spectral Transformer

Hu Bingdong1,2
Wang Tonghan1,2
Jia Huizhen1,2
1. School of Artificial Intelligence and Information Engineering, East China University of Technology, Nanchang 330013, China
2. Jiangxi Engineering Technology Research Center of Nuclear Geoscience Data Science and System, Nanchang 330013, China
DOI: 10.19734/j.issn.1001-3695.2025.10.0444

Abstract

Due to the difficulty of obtaining Mean Opinion Scores (MOS) for hyperspectral image (HSI) , Current no-reference hyperspectral image quality assessment (NR-HSIQA) methods often rely on natural scene statistics to avoid dependence on MOS labels, which makes it difficult to capture the complex spatial-spectral distortion relationships inhyperspectral images. To address these issues, this study proposed a weakly supervised NR-HSIQA model based on a spatial-spectral bidirectional modulation Transformer. The model integrated multiple full-reference metrics to genera-te pseudo-quality scores and constructed a weakly supervised framework that avoided the need for MOS labels and enabled large-scale training. It designed a dual-branch Transformer architecture to achieve deep fusion of spectral an-d spatial features through cross-dimensional statistical modulation. It introduced a combined ranking-regression optim-ization strategy to enhance quality discrimination and cross-domain generalization. Experiments on two public dataset-s demonstrate that the proposed method requires no MOS labels and achieves higher consistency with various full-r-eference metrics compared to existing approaches.

Foundation Support

国家自然科学基金资助项目(62261001,62266001)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.10.0444
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 7

Publish History

[2026-03-16] Accepted Paper

Cite This Article

胡柄东, 王同罕, 贾惠珍. 基于弱监督和空-谱双向调制Transformer的无参考高光谱图像质量评价 [J]. 计算机应用研究, 2026, 43 (7). (2026-03-24). https://doi.org/10.19734/j.issn.1001-3695.2025.10.0444. (Hu Bingdong, Wang Tonghan, Jia Huizhen. No-reference hyperspectral image quality assessment with weakly-supervised and bidirectional spatial-spectral Transformer [J]. Application Research of Computers, 2026, 43 (7). (2026-03-24). https://doi.org/10.19734/j.issn.1001-3695.2025.10.0444. )

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  • Application Research of Computers Monthly Journal
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    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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