التفاصيل البيبلوغرافية
| العنوان: |
Single Infrared Image Stripe Removal via Residual Attention Network |
| المؤلفون: |
Dan Ding, Ye Li, Peng Zhao, Kaitai Li, Sheng Jiang, Yanxiu Liu |
| المصدر: |
Sensors; Volume 22; Issue 22; Pages: 8734 |
| بيانات النشر: |
Multidisciplinary Digital Publishing Institute |
| سنة النشر: |
2022 |
| المجموعة: |
MDPI Open Access Publishing |
| مصطلحات موضوعية: |
infrared image, non-uniformity correction, multi-scale feature, similarity metric, attention mechanism |
| الوصف: |
The non-uniformity of the readout circuit response in the infrared focal plane array unit detector can result in fixed pattern noise with stripe, which seriously affects the quality of the infrared images. Considering the problems of existing non-uniformity correction, such as the loss of image detail and edge blurring, a multi-scale residual network with attention mechanism is proposed for single infrared image stripe noise removal. A multi-scale feature representation module is designed to decompose the original image into varying scales to obtain more image information. The product of the direction structure similarity parameter and the Gaussian weighted Mahalanobis distance is used as the similarity metric; a channel spatial attention mechanism based on similarity (CSAS) ensures the extraction of a more discriminative channel and spatial feature. The method is employed to eliminate the stripe noise in the vertical and horizontal directions, respectively, while preserving the edge texture information of the image. The experimental results show that the proposed method outperforms four state-of-the-art methods by a large margin in terms of the qualitative and quantitative assessments. One hundred infrared images with different simulated noise intensities are applied to verify the performance of our method, and the result shows that the average peak signal-to-noise ratio and average structural similarity of the corrected image exceed 40.08 dB and 0.98, respectively. |
| نوع الوثيقة: |
text |
| وصف الملف: |
application/pdf |
| اللغة: |
English |
| العلاقة: |
Sensing and Imaging; https://dx.doi.org/10.3390/s22228734Test |
| DOI: |
10.3390/s22228734 |
| الإتاحة: |
https://doi.org/10.3390/s22228734Test |
| حقوق: |
https://creativecommons.org/licenses/by/4.0Test/ |
| رقم الانضمام: |
edsbas.BA932ADA |
| قاعدة البيانات: |
BASE |
