Line Scan Hyperspectral Imaging Framework for Open Source Low-Cost Platforms

Round 1

Reviewer 1 Report

The manuscript (remotesensing-2329802) is interesting and demonstrates a new approach. With advancements in computer processing power and deep learning techniques, hyperspectral imaging continues to be explored for improved sensing applications across various fields. However, the high cost associated with such imaging platforms limits their widespread use, despite the availability of necessary processing power. This paper presents a novel theoretical framework for an open-source, ultralow-cost hyperspectral imaging platform based on the line scan method that is suitable for remote sensing applications. The authors demonstrate the design and fabrication of an open-source platform using affordable and easily accessible consumer-grade commercial off-the-shelf components. The optical system incorporates a consumer-grade spectroscope and a basic galvanometer mirror commonly used in laser scanning devices. The employed pushbroom scanning method offers a high spectral resolution of 2.8 nm, tested against commercial spectral sensors. As the resolution is limited by the spectroscope's slit width, the authors also provide a deconvolution method to improve monochromatic spatial resolution. Finally, a cost-effective testing method is presented, validating both the spectral and spatial performance of the platform.

However, I have some questions for authors:

How does the performance of the ultralow-cost hyperspectral imaging platform compare with more expensive, commercially available platforms in terms of accuracy and reliability?

What are the limitations of the proposed ultralow-cost hyperspectral imaging platform in terms of operating conditions, such as temperature, humidity, and ambient light?

How does the open-source nature of the platform affect the potential for customization and adaptation to specific remote sensing applications or other fields?

Are there any challenges in terms of data storage and processing due to the potentially large volume of hyperspectral data generated by the platform?

How can the ultralow-cost hyperspectral imaging platform be integrated into existing remote sensing workflows or systems?

What potential advancements in hardware or software could further improve the performance or capabilities of the proposed platform in the future?

Are there any specific applications or research areas where the ultralow-cost hyperspectral imaging platform could provide unique benefits or advantages compared to traditional imaging systems?

Additionally, have the authors tested the ultralow-cost hyperspectral imaging platform on other biological and material models besides those reported in this manuscript?

Best regards,

Author Response

Many thanks for the excellent comments. kindly find attached response (PDF)

Author Response File: Author Response.pdf

Reviewer 2 Report

The authors developed an open-source ultra-low-cost hyperspectral imaging platform based on the line-scan method and theoretical framework. This paper sounds technical correct and is of practical application. I suggest a minor revision. Some detailed suggestions are shown as follows.

1.     Since ultra-low cost is a major contribution to the full text, I think the section 4.1 "Cost and build time" can be expanded into more space to introduce. For instance, Make more specific statements about the monetary cost of each component, so that the advantages can be more prominent.

2.     The author mentions that the device assembly time depends on the individual experience of the assembler. I suggest that the authors come up with some more practical suggestions in section 4.1.

3.     In fig.8 and fig.9, the annotation of the tables are not centered, but are further to the left compared to the figures. My suggestion is to center the table's annotations.

4.     In the left half of fig.10, the coordinate axes of the graph indicate that vertical writing is not conducive to reading. I recommend writing "Normalized power spectral density" horizontally.

5.     Sec. 2.1.1 contains only one excessively long paragraph. I recommend breaking up that long paragraph into several smaller ones.

Author Response

Many thanks for the excellent comments. kindly find attached response (PDF)

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments for author File: Comments.pdf

Author Response

Many thanks for the excellent comments. kindly find attached response (PDF)

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

Comments for author File: Comments.pdf

Author Response

Thanks for the positive comments, please find the response in the attached document.

Author Response File: Author Response.pdf