Single Infrared Image Stripe Noise Removal Using Deep Convolutional Networks
In this paper, we present a deep learning method for single infrared image stripe noise removal. Our method is denoted as a deep convolutional neural network (CNN) that takes the noisy image as the input and outputs the clean image. The deep CNN consists of two components: 1) image denoising, substa...
I tiakina i:
| Ngā kaituhi matua: | , , , |
|---|---|
| Hōputu: | Tuhinga |
| Reo: | Ingarihi |
| I whakaputaina: |
IEEE
2017-01-01
|
| Rangatū: | IEEE Photonics Journal |
| Ngā marau: | |
| Urunga tuihono: | https://ieeexplore.ieee.org/document/7954611/ |
| Tags: |
Tāpirihia he Tūtohu
No Tags, Be the first to tag this record!
|
| Whakarāpopototanga: | In this paper, we present a deep learning method for single infrared image stripe noise removal. Our method is denoted as a deep convolutional neural network (CNN) that takes the noisy image as the input and outputs the clean image. The deep CNN consists of two components: 1) image denoising, substantially removing the stripe noise but losing details, 2) image denoising and super resolution, completely eliminating the residual stripe noise and restore details. Our deep CNN exhibits excellent image denoising and detail preserving performance. Meanwhile it achieves fast speed for real-time image processing. Experiments study the relationship between model parameter settings and model performance. |
|---|---|
| ISSN: | 1943-0655 |