Acta Optica Sinica, Volume. 40, Issue 21, 2111001(2020)
Deep Learning Based Image Restoration Method of Optical Synthetic Aperture Imaging System
[1] Barakat R. Dilute aperture diffraction imagery and object reconstruction[J]. Optical Engineering, 29, 131-139(1990).
[4] Bell K D, Boucher R H, Vacek R et al. Assessment of large aperture lightweight imaging concepts[C]//1996 IEEE Aerospace Applications Conference. Proceedings, February 10, 1996, Aspen, CO, USA., 187-203(1996).
[5] Fienup J R, Griffith D K, Harrington L et al. Comparison of reconstruction algorithms for images from sparse-aperture systems[J]. Proceedings of SPIE, 4792, 1-8(2002).
[6] Wang D, Han J, Liu H et al. Experimental study on imaging and image restoration of optical sparse aperture systems[J]. Optical Engineering, 46, 103201(2007).
[7] Wu Q Y, Qian L, Shen W M. Image recovering for sparse-aperture systems[J]. Proceedings of SPIE, 5642, 478-486(2005).
[8] Liu L, Jiang Y S, Wang C W. Noise analysis and image restoration for optical sparse aperture systems[C]//2008 International Workshop on Education Technology and Training & 2008 International Workshop on Geoscience and Remote, 353-356(2008).
[11] Wang F, Jiang M Q, Qian C et al. Residual attention network for image classification[C]//2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA., 6450-6458(2017).
[13] Rivenson Y, Koydemir H C, Wang H et al. Deep learning enhanced mobile-phone microscopy[J]. ACS Photonics, 5, 2354-2364(2018).
[16] Zhang K, Zuo W M, Chen Y J et al. Beyond a Gaussian denoiser: residual learning of deep CNN for image denoising[J]. IEEE Transactions on Image Processing, 26, 3142-3155(2017).
[17] Yan K T, Yu Y J, Huang C T et al. Fringe pattern denoising based on deep learning[J]. Optics Communications, 437, 148-152(2019).
[18] Wang K Q, Dou J Z, Qian K M et al. Y-Net: a one-to-two deep learning framework for digital holographic reconstruction[J]. Optics Letters, 44, 4765-4768(2019).
[20] Wang K Q, Li Y, Qian K M et al. One-step robust deep learning phase unwrapping[J]. Optics Express, 27, 15100-15115(2019).
[21] Wang K Q, Di J L, Li Y et al. Transport of intensity equation from a single intensity image via deep learning[J]. Optics and Lasers in Engineering, 134, 106233(2020).
[23] Xu W H, Zhao M, Li H S. Non-iterative wavelet-based deconvolution for sparse aperture system[J]. Optics Communications, 295, 36-44(2013).
[24] Kundur D, Hatzinakos D. Blind image deconvolution[J]. IEEE Signal Processing Magazine, 13, 43-64(1996).
[25] Kundur D, Hatzinakos D. A novel blind deconvolution scheme for image restoration using recursive filtering[J]. IEEE Transactions on Signal Processing, 46, 375-390(1998).
[26] Yang H L, Chiao Y H, Huang P H et al. Blind image deblurring with modified Richardson-Lucy deconvolution for ringing artifact suppression. [C]// Proceedings of the 5th Pacific Rim conference on Advances in Image and Video Technology, November 20-23, 2011, Heidelberg: Springer, 240-251(2011).
[27] Ronneberger O, Fischer P, Brox T[M]. U-net: convolutional networks for biomedical image segmentation, 234-241(2015).
[29] Srivastava N, Hinton G E, Krizhevsky A et al. Dropout: a simple way to prevent neural networks from overfitting[J]. Journal of Machine Learning Research, 15, 1929-1958(2014).
[30] [30] HoréA, ZiouD. Image quality metrics: PSNR vs. SSIM[C]//2010 20th International Conference on Pattern Recognition, August 23-26, 2010, Istanbul, Turkey. New York: IEEE Press, 2010: 2366- 2369.
[31] Cheng G, Han J W, Lu X Q. Remote sensing image scene classification: benchmark and state of the art[J]. Proceedings of the IEEE, 105, 1865-1883(2017).
Get Citation
Copy Citation Text
Ju Tang, Kaiqiang Wang, Wei Zhang, Xiaoyan Wu, Guodong Liu, Jianglei Di, Jianlin Zhao. Deep Learning Based Image Restoration Method of Optical Synthetic Aperture Imaging System[J]. Acta Optica Sinica, 2020, 40(21): 2111001
Category: Imaging Systems
Received: Jun. 19, 2020
Accepted: Jul. 15, 2020
Published Online: Oct. 17, 2020
The Author Email: Di Jianglei (jiangleidi@nwpu.edu.cn), Zhao Jianlin (jlzhao@nwpu.edu.cn)