A Novel Automatic Registration Method for Array InSAR Point Clouds in Urban Scenes

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This manuscript analyzes the error characteristics of array InSAR point clouds and proposes a robust registration method for array InSAR point clouds in urban scenes. This method is applied to the point cloud in Emei area and obtain good results. The overall layout of the manuscript is reasonable, and the language expression is concise and standardized. However, the manuscript should be improved in the follow aspects.

1. The stability and generalization of this method face many challenges. SMRF and KAZE algorithm are sensitive to parameters. The method flow is complicated. Although urban areas are mostly flat, the assumption that the ground is horizontal limits the application range of this method.

2. The learning-based point cloud registration method has been extensively studied and deeply developed, but it is not mentioned in the introduction.

3. There are some small mistakes in the manuscript. Figure 10d in line 369 should be the result of the second flight. In equation 2, B means the length of baseline, which should be explained after the equation. The y-axis of the PDF should be the probability density.

Author Response

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Reviewer 2 Report

Comments and Suggestions for Authors

This paper proposes a registration method for array InSAR point clouds in urban scene. Its performance is tested by two real point cloud data. Some comments are as follows：

Line-100 “The aforementioned methods are widely applied in the registration of laser point clouds…”This paper proposes a registration method for array InSAR point clouds. However, there are more related articles for the registration of laser point clouds in Introduction.

Line-122: A literature is missing for the KAZE algorithm.

The manuscript presents the steps of the proposed method clearly. However, further summary of its innovation is needed.

Line-355: The Figure 9 and its name are on separate pages.

The experiments nicely show the results obtained by the proposed method, but there are only two existing methods used for comparison.

Author Response

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Reviewer 3 Report

Comments and Suggestions for Authors

This article presented a method to automatically register the corresponding points of array InSAR point clouds and this method was tested with airborne image in urban area. The idea of this article is interesting to the readers but there are some issues in the current version of manuscript. I would ask the authors improve the article and then the decision for publication is going to make.

I would suggest the authors check the following issues to improve the manuscript.

1.     There was no explanation about KAZE. This acronym should be given a full name when it appears at the first time. Was the KAZE invented by the authors or introduced from the literature?  

2.     Check the title of fig 10. Were all subimages from the first flight？

3.     Is there a need to have a legend to visualize the 3d images?

4.     In fig 14 and 17, the matched points were not well distributed and the number of points were also limited. How did the result become better in this scenario? Were the matched points used to geometrically register two images？The illustrations in the article for the matched points did not represent the best algorithm.

 

5.     The conclusion section was not well written. The key steps about the proposed method should be presented again. The key findings should be highlighted and given the quantitive evaluation.

Comments on the Quality of English Language

in general, the English language is fine but there are some sentences to be polished. 

Author Response

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