دورية أكاديمية
Ghost edge detection based on HED network
| العنوان: | Ghost edge detection based on HED network |
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| المؤلفون: | Shengmei Zhao, Yifang Cui, Xing He, Le Wang |
| المصدر: | Frontiers of Optoelectronics, Vol 15, Iss 1, Pp 1-9 (2022) |
| بيانات النشر: | Springer & Higher Education Press, 2022. |
| سنة النشر: | 2022 |
| المجموعة: | LCC:Applied optics. Photonics |
| مصطلحات موضوعية: | Edge detection, Ghost imaging (GI), Holistically-nested neural network, Compression ratio (CR), Signal-to-noise ratio (SNR), Applied optics. Photonics, TA1501-1820 |
| الوصف: | Abstract In this paper, we present an edge detection scheme based on ghost imaging (GI) with a holistically-nested neural network. The so-called holistically-nested edge detection (HED) network is adopted to combine the fully convolutional neural network (CNN) with deep supervision to learn image edges effectively. Simulated data are used to train the HED network, and the unknown object’s edge information is reconstructed from the experimental data. The experiment results show that, when the compression ratio (CR) is 12.5%, this scheme can obtain a high-quality edge information with a sub-Nyquist sampling ratio and has a better performance than those using speckle-shifting GI (SSGI), compressed ghost edge imaging (CGEI) and subpixel-shifted GI (SPSGI). Indeed, the proposed scheme can have a good signal-to-noise ratio performance even if the sub-Nyquist sampling ratio is greater than 5.45%. Since the HED network is trained by numerical simulations before the experiment, this proposed method provides a promising way for achieving edge detection with small measurement times and low time cost. Graphical Abstract |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2095-2759 2095-2767 |
| العلاقة: | https://doaj.org/toc/2095-2759Test; https://doaj.org/toc/2095-2767Test |
| DOI: | 10.1007/s12200-022-00036-1 |
| الوصول الحر: | https://doaj.org/article/33bf0626652d4edcb935effb360ed4a5Test |
| رقم الانضمام: | edsdoj.33bf0626652d4edcb935effb360ed4a5 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 20952759 20952767 |
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| DOI: | 10.1007/s12200-022-00036-1 |