Efficient On-Board Compression for Arbitrary-Shaped Cloud-Covered Remote Sensing Images via Adaptive Filling and Controllable Quantization

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript presents an efficient compression scheme tailored for cloud-covered remote sensing images, featuring key strategies such as Optimized Adaptive Filling (OAF) and Controllable Quantification (CQ). This work offers valuable technical insights for the efficient storage and transmission of high-resolution remote sensing imagery.

However, there are several areas where the manuscript could be improved:

1. It would be beneficial to include an analysis, discussion, or evaluation evidence demonstrating the suitability of the proposed methods for on-board applications.

2. The manuscript should provide a more comprehensive description of the proposed solution, including how the cloud masks are reliably obtained and the selection mechanism for the parallel OAF and CQ modules.

3. According to Table 3, JBIG1 shows a more pronounced advantage in binary image encoding. It is recommended that the manuscript provide a more insightful discussion on the value of the proposed methods in this context.

4. The experimental section only evaluates the proposed OTF and CQ strategies in conjunction with the JPEG2000 codec. It would be useful to explore how these methods perform when combined with other codecs and to report on the potential performance outcomes.

5. The manuscript should compare the overall advantages of the proposed methods against other lossy compression frameworks, including state-of-the-art handcraft designed codecs and learning-based codecs, specifically in the context of compressing cloud-covered remote sensing images.

6. The meaning of the column headers in Table 1 is unclear from the context of the manuscript. It is recommended that the headers be explained more clearly to enhance understanding.

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

What is the main need and challenge presented by the proposed on-board compression method for remote sensing data?

 

The key components of the proposed compression method look like the conventional method. What is new about the proposed method?

 

How is the Optimized Adaptive Filling (OAF) strategy responsible for the efficient compression?

 

What is the role of the Controllable Quantification (CQ) strategy that can be further utilized for the processing of thin cloud images?

 

How does the proposed method handle the binary cloud mask to improve compression efficiency?

 

What are the advantages of embedding the proposed preprocessing strategies into existing compression frameworks like JPEG2000, it the proposed methodology is limited to jpg only?

 

 

How experimental results of the proposed method on the GF-1 dataset, applied to the other datasets?

Comments for author File: Comments.pdf

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The overall quality of the manuscript is high. The method is clearly described. The authors provide an extensive performance evaluation of the proposed technique. A performance comparison against other methods is conducted.

 

Some points to be considered by the authors:

- In lines 24 and 25, it does not seem reasonable to have the word "current" associated with a reference from 2017.

-  In line 27, "more suitable choice" in comparison with what?

- In line 160, "good" seems to be vague.

- In equation (8), lg must be replaced by log. 

- Equations must be punctuated (period or comma).

 

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The revised manuscript presents a valuable approach to on-board remote sensing image compression systems. It offers significant insights and practical solutions relevant to the field. I recommend accepting it for publication.