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Article
Peer-Review Record

Underwater Image Enhancement Based on Multi-Scale Fusion and Global Stretching of Dual-Model

Mathematics 2021, 9(6), 595; https://doi.org/10.3390/math9060595
by Huajun Song * and Rui Wang
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Mathematics 2021, 9(6), 595; https://doi.org/10.3390/math9060595
Submission received: 29 January 2021 / Revised: 20 February 2021 / Accepted: 23 February 2021 / Published: 10 March 2021
(This article belongs to the Special Issue Computer Graphics, Image Processing and Artificial Intelligence)

Round 1

Reviewer 1 Report

Authors proposes an underwater image enhancement method based on MFGS. The reality is that the underwater image must have a lot of noise. This study has well organized studies suitable for a specific field. In particular, the qualitative and evaluation excellence of the proposed technology is well compared with other previous studies to explain.
Finally, if the resolution and execution time of the experimental image are additionally described, it is considered a good paper.
Minor English problems must also be solved.

Author Response

Thank you for your suggestions.

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

The manuscript entitled: Underwater Image Enhancement Based on Multi-Scale Fusion 2 and Global Stretching of Dual-Model presents very interesting scientific aspects on the topic of Underwater Image Enhancement. With the advent of photogrammetry, Image Enhancement plays a very important role because the colour correction allows to restore the quality and intelligibility of images and this aspect is of great interest to biologists and archaeologists. With regard to the manuscript to make it more organic and better-structured work done we suggest the authors to integrate the introduction of the manuscript with additional bibliography on 'Underwater Image Enhancement as an example we report the following manuscripts:

Mangeruga, M., Cozza, M., & Bruno, F. (2018). Evaluation of underwater image enhancement algorithms under different environmental conditions. Journal of Marine Science and Engineering, 6(1), 10.

Mangeruga, M., Bruno, F., Cozza, M., Agrafiotis, P., & Skarlatos, D. (2018). Guidelines for underwater image enhancement based on benchmarking of different methods. Remote Sensing10(10), 1652.

Schettini, R., & Corchs, S. (2010). Underwater image processing: state of the art of restoration and image enhancement methods. EURASIP Journal on Advances in Signal Processing, 2010, 1-14.

Anwar, S., & Li, C. (2020). Diving deeper into underwater image enhancement: A survey. Signal Processing: Image Communication89, 115978.

Hou, G., Zhao, X., Pan, Z., Yang, H., Tan, L., & Li, J. (2020). Benchmarking underwater image enhancement and restoration, and beyond. IEEE Access, 8, 122078-122091.

Han, F., Yao, J., Zhu, H., & Wang, C. (2020). Underwater image processing and object detection based on deep CNN Method. Journal of Sensors, 2020.

Comparison with other similar work is necessary to better highlight the innovation of your experimentation and this must be well addressed in the discussion and conclusion

On line 102 - 105 modify the following text:

The rest of the paper is organized as follows. In section 2, three stages of the underwater image enhancement algorithm are introduced in detail. Section 3 shows the results of the qualitative and quantitative comparison of the proposed, classical, state-of-the-art methods. Finally, the conclusions are stated in section 4.

With the following:

This paper will discuss the three phases of the underwater image enhancement algorithm and the results of the qualitative and quantitative comparison of the proposed classical and state-of-the-art methods will be shown.

 

We also ask the authors of the manuscript to revise the methodological description of Multi-Scale Fusion2 and Global Stretching of Dual-Model making it much clearer, so that the main features of the processing type emerge. 

It is recommended to include a discussion paragraph where the results obtained from your experimentation are compared with other underwater imaging methods.

We ask you to integrate the conclusions with more elements and information in order to highlight the main results obtained, possibly also the gaps and if there are future perspectives for your Multi-Scale Fusion2 and Global Stretching of Dual-Model algorithm.

Author Response

Thank you for your suggestions.

Please see the attachment.

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

Congratulations to the authors of the manuscript entitled: Underwater Image Enhancement Based on Multi-Scale Fusion and Global Stretching of Dual-Model, for appreciating and valuing the proposed comments and revisions. The article can be accepted in its current form.

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