Online Learning for Reference-Based Super-Resolution
Round 1
Reviewer 1 Report
1、There are many formatting problems in the article, such as the misplacement of the title row of the table, I hope the author can check it carefully.
2、The experimental part of the article is not perfect, I hope the author can add several comparison algorithms
3、There are some problems with the reference format, hope the author can double check.
4、There are some grammar problems in this article, I hope the author can check it carefully.
5、The author's references are somewhat lacking, I hope the author can introduce three or more related papers in the references, such as:
A novel point-matching algorithm based on fast sample consensus for image registration.
Commonality Autoencoder: Learning Common Features for Change Detection From Heterogeneous Images.
A Two-Step Method for Remote Sensing Images Registration Based on Local and Global Constraints.
Author Response
Please see the attachment.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Authors suggested online learning for superresolution. The idea is reasonable. Authors have presented experiments. This work may be accepted for publication subject to following:
- Detail description of methods should be presented. It should clearly point out technical contributions on the online learning front. Algorithm(s) should also be added for better representation.
- More results both visual and quantitative would make the manuscript more valuable. In particular, results should highlight how online learning impacted SR processes.
- Kindly get it corrected for usage of English language.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
no comment
