دورية أكاديمية

Sharpening algorithm for underground images with fog and dust

التفاصيل البيبلوغرافية
العنوان: Sharpening algorithm for underground images with fog and dust
المؤلفون: WU Kaixing, ZHANG Lin, LI Lihong
المصدر: Gong-kuang zidonghua, Vol 44, Iss 3, Pp 70-75 (2018)
بيانات النشر: Editorial Department of Industry and Mine Automation, 2018.
سنة النشر: 2018
المجموعة: LCC:Mining engineering. Metallurgy
مصطلحات موضوعية: underground video surveillance, fog and dust image, sharpening algorithm, dark primary principle, principal component analysis, Mining engineering. Metallurgy, TN1-997
الوصف: In view of fuzzy and degenerated images in coal mine environment due to presence of large amounts of coal dust and water mist, a sharpening algorithm based on dark primary principle and principal component analysis was proposed. Based on atmospheric scattering model, transmittance is calculated according to the dark primary principle. The principal component analysis is used to obtain brightness, saturation and contrast, which can fully reflect fog image information. Atmospheric light value is calculated by weighting these indexes, so as to realize sharpening process of underground images with fog and dust in underground coal mine. The simulation results show that the proposed algorithm can restrain image detail to a great extent, maintain authenticity and structural integrity of the image, and have good real-time performance.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: Chinese
تدمد: 1671-251X
1671-251x
Relation: https://doaj.org/toc/1671-251X
DOI: 10.13272/j.issn.1671-251x.2017100078
URL الوصول: https://doaj.org/article/6330d331c74545089538c8b68daa5316
رقم الأكسشن: edsdoj.6330d331c74545089538c8b68daa5316
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:1671251X
1671251x
DOI:10.13272/j.issn.1671-251x.2017100078