دورية أكاديمية

Adaptive Dark Channel Prior Enhancement Algorithm for Different Source Night Vision Halation Images

التفاصيل البيبلوغرافية
العنوان: Adaptive Dark Channel Prior Enhancement Algorithm for Different Source Night Vision Halation Images
المؤلفون: Quanmin Guo, Hanlei Wang, Jianhua Yang
المصدر: IEEE Access, Vol 10, Pp 92726-92739 (2022)
بيانات النشر: IEEE, 2022.
سنة النشر: 2022
المجموعة: LCC:Electrical engineering. Electronics. Nuclear engineering
مصطلحات موضوعية: Night vision halation image, different source image, dark primary color prior enhancement, adaptive enhancement, image fusion, anti-halation, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
الوصف: The existing enhancement algorithms amplify the halation area and noise when enhancing the night vision halation image. Therefore, this paper proposes an adaptive dark channel prior (ADCP) enhancement algorithm for the different source night vision halation image. The algorithm constructs an adaptive transmittance function according to the relationship between the initial transmittance and the critical gray value of halation. The function can automatically adjust the transmittance according to the halation degree in the night vision image, which ensure the ADCP algorithm to achieve the adaptive enhancement of the images. The experimental results show that the proposed algorithm can effectively improve the clarity and contrast of visible and infrared images in night vision, and avoid over-enhancement of the halation region of visible images. When the proposed algorithm is applied to the anti-halation processing of different source night vision image fusion, the halation elimination of the fused image is more complete, the details of the dark area such as edge, brightness and color are moderately improved, and the overall visual effect is better than the existing enhancement algorithms. The effectiveness and universality of the proposed algorithm are verified for processing different night vision halation scene images.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2169-3536
Relation: https://ieeexplore.ieee.org/document/9870776/; https://doaj.org/toc/2169-3536
DOI: 10.1109/ACCESS.2022.3203183
URL الوصول: https://doaj.org/article/04ba00826645480dbd822a2aad2b486d
رقم الأكسشن: edsdoj.04ba00826645480dbd822a2aad2b486d
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:21693536
DOI:10.1109/ACCESS.2022.3203183