High Bandwidth-Utilization Digital Holographic Reconstruction Using an Untrained Neural Network
, Yuanyuan Chen 1,2,3, Jiasong Sun 1,2,3, Yanbo Jin 1,2,3, Qian Shen 1,2,3, Peng Gao 4,*, Qian Chen 3 and Chao Zuo 1,2,3,*
Round 1
Reviewer 1 Report
Comments for author File: 
Comments.pdf
Author Response
Thank you for your constructive suggestions and valuable comments. For the points you raised and the suggestions, I have given to explain in my response and revised my manuscript. Please see the attachment.
Author Response File: 
Author Response.docx
Reviewer 2 Report
In the present manuscript, the authors propose a low-carrier frequency fringe demodulation method for high SBU DH imaging from a single frame hologram by exploiting the conventional deep neural network with out training beforehand. The validity of the proposed method is demonstrated with simulation and the applicability is demonstrated with experimental data from a slightly off-axis DHM system.
The manuscript is well organized, and the data are coherently presented, starting from the methods, and then to simulation and the real-valued DH imaging. In my opinion the manuscript is suitable for publication in Applied Sciences, and therefore I suggest accepting the paper in its current form.
Author Response
Thank you very much for your recognition of my work, thank you for your affirmation, and I will continue to work hard to contribute to this field.
Reviewer 3 Report
High bandwidth-utilization digital holographic reconstruction using an untrained neural network
This manuscript proposes a simple method by regarding the low-carrier frequency fringe demodualtion as a nonlinear optimization problem. The network can reconstruct the artifact-free phase details gradually from a single-grame hologram. The live-cell experiments demonstrate the method and the results are interesting to a general audience.
It is suggested to mark the place of object in Figure 1(a).
It is suggested to explain the value range from 0 to 10 in the color bar.
Author Response
Thank you very much for your recognition of my work and affirmation, and I will continue to work hard to contribute to this field. I have revised my manuscript according to your suggestion. If you have any other suggestions, I hope you can do not hesitate to propose them to me.
