Preserving Colour Fidelity in Photogrammetry—An Empirically Grounded Study and Workflow for Cultural Heritage Preservation

Round 1

Reviewer 1 Report

This paper presents an empirical study on preserving color information integrity in cultural heritage photogrammetry. The research focuses on maintaining control over the handling of color information. Various conditions, such as acquisition illumination, raw to RGB conversion, and color spaces, are examined. The study argues that using a larger operational RGB gamut, specifically the wide RGB color space, leads to better color preservation. Controlled illumination conditions, like LED or fluorescent lamps, are found to be beneficial. Manual processes, such as discarding non-Bayer tile pixels or using bilinear interpolation, are preferred over automated machine processes for raw-to-RGB transformation. The study contributes to the preservation of color fidelity in photogrammetry by combining perceptual and objective assessments.

For the improvement of the paper the following are suggested:

Introduction:

-Provide a more explicit statement of the research problem or gap that your paper aims to address. Specify the scope or focus of your proposed method to generate RGB images for photogrammetry and its importance in preserving the true colors of cultural heritage objects.

-Consider rephrasing the sentence: "The paper is structured as the following..." to "The paper is structured as follows..."

Materials and Methods:

-Clarify the purpose of debayering and its importance in transforming raw image data to RGB.

-Explain the advantages and disadvantages of the three debayering procedures listed (direct debayering, bilinear interpolation, discard) and provide a rationale for the selection of the three procedures.

Evaluation

-Consider providing more details about the experimental setups, including the specific lighting conditions (indirect sunlight, fluorescent room light, white LEDs) and the camera and lens used for image acquisition. Moreover you could explain the image acquisition process, such as the number of images taken per object, the positioning of the camera and lighting equipment, and any specific considerations for capturing the objects.

-Specify how the configurations tested (36 configurations) were determined based on the different debayering techniques, color spaces, and acquisition steps.

Results

-Discuss the implications of the debayering techniques on the color preservation and the observed differences in the results. Provide a rationale for choosing one technique over another.

Author Response

Dear Reviewer 1,

Thank you for your time and effort. We provide answers to your comments and concerns and have reviewed the manuscript accordingly. The corrections are marked in red in the manuscript.

Introduction:

-Provide a more explicit statement of the research problem or gap that your paper aims to address. Specify the scope or focus of your proposed method to generate RGB images for photogrammetry and its importance in preserving the true colors of cultural heritage objects.

Answer: Following your kind suggestion, we have included a new paragraph in the introduction that clarifies our aim with he paper, and also added another sentence to the abstract so the research gap is clearly noticed from the beginning on.

Added text:

Abstract: “This paper aims to serve as guidelines of a correct handling of colour information and workflow so cultural heritage documentation can be performed with the highest degree of colour fidelity, covering the gap of nonexisting standard procedure or conditions to perform an optimum digital cultural heritage colour modelling.”

Introduction: “Nevertheless, in spite of the importance of preserving the integrity of visual characteristics in digital cultural heritage modelling, there exist no standard or preferred procedure to achieve it on a holistic level. As such, the work in this paper aims therefore to serve as guidelines to perform a digital cultural heritage 3D modelling process of minimal quality loss, and incorporates an adaptive type of colour calibration employed in previous works that ensures state-of-the-art accuracy in homogenizing colour between pictures. The given guidelines are easy to follow and implement, do not require overly specialized gear or expensive purchases, and are designed so any cultural heritage preservation laboratory can follow them with basic installations and procedures”

-Consider rephrasing the sentence: "The paper is structured as the following..." to "The paper is structured as follows..."

Answer: We are thankful to you for noticing this mistake in expression, as English is not our native language. We will double check the grammar and orthography so we ensure the text bears a good readability.

Materials and Methods:

-Clarify the purpose of debayering and its importance in transforming raw image data to RGB.

Answer: Your comment has clarified us that there was a need for a theoretical introduction to debayering so any reader can understand why this procedure has been chosen. We have added some paragraphs at the beginning of the section so its importance is highlighted.

Added text:

“Any digital camera can retrieve the acquired scene in form of digital RGB data, but only as a the result of a mathematically delicate process that transforms the light inciding in the objective into presentation-ready digits - precisely the same process that can imply the compression and information loss this work intends to avoid. Therefore, a manual  handling of data is performed.

The most immediate data that can be recovered from any camera are the direct digitalization of the captured light, also known as raw data. Usually, they would be automatically transformed and processed into RGB, in a sub-process known as debayering. Then, these intermediate RGB data (known as Camera RGB) would be compressed and further processed until the final results.

The aim of this step is to directly transform the original raw image data to RGB by imitating the functioning of the camera's internal optoelectronic block, according to the colour Filter Array (CFA) of the camera, while avoiding any other further operation that could jeopardise the captured colour's integrity.”

-Explain the advantages and disadvantages of the three debayering procedures listed (direct debayering, bilinear interpolation, discard) and provide a rationale for the selection of the three procedures.

Answer: Following your suggestion, we have improved reasons of choice and the explanations of the debayering techniques highlighting their most important advantages and disadvantages in the context of the presented work.

Added text:

“The chosen debayering approaches have been considered due to their default easiness to implement, their theoretical quality, and the fact that they milden the effect of fabricating "new" information in the interpolated pixels: bilinear interpolation assures an average between neighbours instead of their repetition or the introduction of non-linearities.”

“1. Direct debayering: direct debayering of the raw image data of the NEF format based on standard procedure following the Python RawPy library. Its concrete algorithm is "Adaptive homogeneity-directed demosaicing algorithm" ("AHD"). It features the advantage of estimating the colour by minimizing artifacts and errors; however, its conception based in filter banks makes the process non-linear, and additionally loses a small stripe of pixels due to convolution operations.

2. Bilinear interpolation: respecting the original pixel size of the raw image, the non-valid pixels are substituted by a bilinear interpolation of the Bayer tiles pixels. It has the advantages of linearity - and therefore reversability - and the fact that the full size of the image is saved. The disadvantage may be a bigger risk of the production of colour artifacts due to its simple conception.

3. Discard: all non-valid pixels are discarded, and the resulting image is one quarter of the size of the original raw file. Its obvious advantage is that no new information is fabricated, therefore all saved pictures bear true information. The disadvantage is effectively, the loss of information, while it may ease calculations due to its reduced size.”

Evaluation

-Consider providing more details about the experimental setups, including the specific lighting conditions (indirect sunlight, fluorescent room light, white LEDs) and the camera and lens used for image acquisition. Moreover you could explain the image acquisition process, such as the number of images taken per object, the positioning of the camera and lighting equipment, and any specific considerations for capturing the objects.

Answer: Thank you for your interest in the particular acquisition details. In Section 4, information about the cameras, lenses, illumination and acquisition process are found in the text as well as in Table 2. The positioning of camera and lighting equipment is also mentioned in the text and shown in Figure 6.
A few lines elaborating the acquisition process of the Etruscan mirrors were added, as some specific considerations were made there.

Added text:

“for oblique rotation angles where it was not possible to keep the whole object in focus, multiple images with different focal planes were acquired. As the mirrors had to be fixed with a block of Ethafoam, capturing the whole surface requires to perform two imaging round with the mirror turned upside down in between and then merge the results. However, for the sake of these experiments, we use only one set of images per mirror (see right of Figure~4 for an example”

-Specify how the configurations tested (36 configurations) were determined based on the different debayering techniques, color spaces, and acquisition steps.

Answer: We are thankful for your remark. We have made sure to mention  all parameters that compose the experimental configurations, so it is clarified how the different debayerings, colour spaces and acquisition settings are combined.

Added text:

“Thus, the experimental setup will consist in building textured 3D models in unique combinations of three different debayering techniques (Direct, Bilinear and Discard), three colour RGB spaces (sRGB, Adobe RGB and wide RGB) and four acquisition settings (Mixed, Sun, LED and Fluor) - in total 36 configurations.”

Results:

-Discuss the implications of the debayering techniques on the color preservation and the observed differences in the results. Provide a rationale for choosing one technique over another.

Answer: Thank you very much for your comments and instructions. We expanded the Results section with your indications and we most sincerely hope it will help to improve the quality of our paper even further.

Added text:

“Regarding the debayering techniques, the Direct debayering tends to induce a bigger difference than the Discard and the Interpolated strategies - which stay in the same order of difference. The existence of this phenomenon is favourable to the followed goal of intending to keep control on how the information is processed. The Direct debayering technique, whilst quick, undoubtedly denotes a black box: whilst the demoisaicing algorithm is known, it may incorporate other additional adjustements and transformations, even if some parameters can be adjusted.

The computational cost of photogrammetric reconstruction depends on the size of the input images, such that a common strategy to speed up computations is the reduction of input image size at cost of detail. In such a case, the Discard strategy, in which image size is reduced because only measured colour values are used, is arguably preferable to first creating a full-sized image with an interpolation-based approach and then down-sampling it to the desired size - both in terms of efficiency and original colour preservation.

 However, when a more detailed model is needed, the Interpolation debayering can be employed. Eventhough if the interpolated pixels are "fabricated", the appreciable difference is impeerceptible.

The Discard debayering therefore implies the advantage of quick, light calculation and best results without the need of fabricating new pixels. Only if an extreme amount of detail is needed in the final models, Interpolation can be used due to its quadruple size without incurring in excessive aberrant colour fabrication."

Reviewer 2 Report

This paper has a novel method that solves the problem of poor image information caused by environmental factors and enhances the authenticity of the image. The paper discusses in detail and has strong logic.

1.      In the related work, the literature review can be more regulated. Firstly, it is sorted vertically according to time, and then horizontally according to the category of research methods for the latest research. In addition, the latest research should be added.

2.      In the conclusion, the language expression is too cumbersome to highlight the innovation of the paper. Suggest refining this section again.

Minor editing of English language required

Author Response

Dear Reviewer 2,

Thank you for your time and effort. We provide answers to your comments and concerns and have reviewed the manuscript accordingly. The corrections are marked in red in the manuscript.

1. In the related work, the literature review can be more regulated. Firstly, it is sorted vertically according to time, and then horizontally according to the category of research methods for the latest research. In addition, the latest research should be added.

Answer: We initially had decided for an incremental order sorted by topic; but you are right that temporal evolution is important too. We have modified the related work accordingly, sorted horizontally by topics and referenced on temporal order, and finishing with the research gap and the most recent researches that our paper offers.

2. In the conclusion, the language expression is too cumbersome to highlight the innovation of the paper.Suggest refining this section again.

Answer: We have rewritten and expanded the conclusions so they are more understandable and the main points clearly recognizable, so we thank you for your remark since it allows us to further increase the quality of the paper.

Added text: “In this paper, an empirical study has been performed in order to deduce the optimum operational conditions for colour information integrity preservation in cultural heritage photogrammetry. Since colour is an important characteristic in material cultural heritage pieces, its preservation during documentation is a crucial aspect. The nature of colour information can be affected by external factors, such as illumination or its digitalization. Therefore, it is especially important to thoroughly know how the operational conditions and employed operations can affect it in order to adequately proceed.

It is desirable to maintain a degree of control on how the information is handled, avoiding therefore operational black boxes.

A variety of conditions has been varied, such as scene illumination, raw to RGB transformation parameters (debayering), or the presentation colour space. A self-made multidimensional calibration process of state-of-art results otro has been employed so any colorimetric bias is removed. Therefore, the image batches used for photogrammetry are homogenized and can represent faithful colour information.

The texture generation stage is the only step in the process automatically made, where the blending of colours from multiple input images is not easily traceable, so its effects are finally evaluated.

Wide RGB has proved to be the most effective colour space at avoiding miscolouring in the final images (by hue saturation at the gamut borders). Additionally, it is also the space that works the best for removing any colorimetric bias in calibration, maintaining texture, and revealing the stablest and highest preservation accuracy. When working together with controlled illumination conditions under LED or fluorescent lamps, which are illuminants of moderate brightness compared to natural sources and temperatures around the central section of the spectrum, the highest quality is achieved.

It has also to be ensured that the reference colours in the colour chart surround the colour values of the captured object in space. Then ,the calibration  will function properly, homogenizing the pictures without provoking miscolourings due to value extrapolations, as seen in the table in the shown and LED sets. The choice of the illumination and chart to use is and will require a careful choice depending on the characteristics of the object.

Another consideration to be taken is the debayering strategy, or the transformation from raw colour values to RGB, imitating the performance of the acquisition camera block. Relying on a simple manual process discarding pixels not covered by the Bayer filter, or peerforming a simple bilinear interpolation, the integrity of information is further preserved compared than relying on automated machine processes. Any subsequent visual enhancement of the raw-to-RGB information is performed within the calibration step, instead of during the debayering. Therefore, any additional operations that might further modify the colour are unnecessary.

With the exposed conclusions, guidelines for the optimum handling of colour information have been established. The reproduction of these steps and conditions in any cultural heritage digitalization process will assure a minimum loss or fabrication of colour, after having studied the characteristics of the object.

Future lines of research will ensure the guidelines on how to properly reproduce and reespect other physical characteristics of the pieces, such as 3D details. Furthermore, an interesting aspect of the presented process is its scalability, and future improvements in colour reproduction technology are compatible with it. The acquired raw data can be transformed to any other existing RGB space, including wider spacees that most likely will be standardized in the future. This will allow updating already made models along time with newer technologies that can improve its quality and documentation experience.”

Reviewer 3 Report

Review report for « Preserving colour Fidelity in Photogrammetry –

An empirically grounded study and workflow for Cultural Heritage Preservation »

This article describes a workflow for the preservation of color fidelity and the creation of 3D models using photogrammetry in the context of digital cultural heritage. Particularly, a focus a first brought on image color calibration before a second part on photogrammetry using the previously calibrated images. The article is both a well-presented tutorial and a description of experiments on color spaces, lighting conditions, and method comparisons, which increases the interest of the article for the research community. However, some important points regarding the data acquisition process, the photogrammetry process and results, and the data conservation in the context of digital cultural heritage, need further explanations or discussions for the readers. I recommend major revisions for this article.

Details comments:

Images have an important role in the context of cultural heritage and two complementary approaches might exist. First, color fidelity of objects, which focuses on the obtention of the correct color of the object for digital conservation, which in turn, is helpful for virtual exposition of the object or to apply on models like 3D shapes. The second approach is to focus on data preparation for analysis, i.e., data transformation providing insights on the object, its history or on its historical period. In this case, color fidelity might not be optimal, but it is not a problem as long as insights can be obtained. This article focuses on color fidelity of objects, with the aim of using RGB images, converted from raw sensor data, to create 3D models by photogrammetry. Experiments presented in the article shows the influence of color spaces (sRGB, Adobe RGB and wide RGB) and wider color spaces seems better according to the presented results. My question is the following: could it be interesting to only conserve raw data for cultural heritage preservation? That would also present the advantage to be flexible enough to be compatible with both previously described approaches.

Also, it is written that “photogrammetry needs RGB images to construct a coloured 3D model” (line 40). Is it not possible to use photogrammetry on raw data and to apply color spaces afterwards if needed? Or is it a software limitation, which only works with RGB images?

It could be interesting to discuss the influence of objective lenses and photosensor over color fidelity. If possible, references should be added to this part, at least to let readers know about this difficult subject and the current trends.

Line 157, I think the authors should write “NEF raw data” as readers might not know that this file format correspond to raw data.

I am impressed by color differences in Figure 9, which highlights the importance of wide color spaces. In this case, waiting for more advanced color spaces in the future seems to be a good choice. Therefore, should raw data be the priority for cultural heritage conservation of images? Or is it necessary to choose only one color space?

Line 355, I think “y” should be “by”.

Figure 12, the 3D model of the color checker seems rough but should be flat. How can an observer be sure that this phenomenon doesn’t occur on the 3D model of the object to conserve?

More generally, how can the 3D model fidelity be evaluated?

Defects are present in the 3D models as explained by the authors. A proposed explanation is stitching defect and blending. I am not sure if it is linked to stitching as generally, stitching defects follow straight lines (corresponding to image border, potentially deformed) and this is not the case for the color checker. Also blending should normally homogenize colors. Could it be not a color problem, but 3D model artifacts based on incorrect evaluation of distance between the camera and the object surface by the software? Or is this distance provided by the user as input for the photogrammetry process?

I really appreciate the four lighting settings (“Sun”, “Fluor”, “LED” and “Mixed”) in the experiments. This highlights the importance of the lighting conditions over the visual aspect and perception of an object. More explanations about the differences of lighting conditions when using a turntable should be added. With rotation of the object, light paths to the object are different in each image, which can have influence on the future registration during the photogrammetry process.

Also, discussion on the most suitable lighting conditions for cultural heritage preservation can be interesting. This part is mainly discussed in the article from an “optimal workflow for photogrammetry” perspective but some objects are designed to interact with sunlight, sometimes at a given hour, such as some temples. In this case, should preserving the cultural heritage requires image acquisition in the lighting conditions expected by the designer or with artificial and control lighting conditions?

Author Response

Dear Reviewer 3,

we thank you for your time and dedication. We have made sure to review our manuscript so your comments and suggestions are included. The changes are marked in red.

1. Images have an important role in the context of cultural heritage and two complementary approaches might exist. First, color fidelity of objects, which focuses on the obtention of the correct color of the object for digital conservation, which in turn, is helpful for virtual exposition of the object or to apply on models like 3D shapes. The second approach is to focus on data preparation for analysis, i.e., data transformation providing insights on the object, its history or on its historical period. In this case, color fidelity might not be optimal, but it is not a problem as long as insights can be obtained. This article focuses on color fidelity of objects, with the aim of using RGB images, converted from raw sensor data, to create 3D models by photogrammetry. Experiments presented in the article shows the influence of color spaces (sRGB, Adobe RGB and wide RGB) and wider color spaces seems better according to the presented results. My question is the following: could it be interesting to only conserve raw data for cultural heritage preservation? That would also present the advantage to be flexible enough to be compatible with both previously described approaches.

Answer:  This question is related to questions 2 and 5. They will all be answered under Answer 5.

2. Also, it is written that “photogrammetry needs RGB images to construct a coloured 3D model” (line 40). Is it not possible to use photogrammetry on raw data and to apply color spaces afterwards if needed? Or is it a software limitation, which only works with RGB images?

Answer:  This question is related to questions 1 and 5. They will all be answered under Answer 5.

3. It could be interesting to discuss the influence of objective lenses and photosensor over color fidelity. If possible, references should be added to this part, at least to let readers know about this difficult subject and the current trends.

This is indeed a certainly interesting and relevant topic. We have included some text in the Related Work section that highlights its importance.

Added text:

“The structural composition of cameras does affect how colour is perceived, and miscapturing the scene due to odd sensor responses is a possibility that may occur. Camera sensors do not have lineal responses in spectrum, so some wavelengths might not be represented in all their intensity - leading to colour faking.

The optic block can present chromaticity aberrations that distorsions the radiation inciding over every pixel in the sensor. It has been proved that this phenomenon occurs due to the chemical and material composition of the sensors and optic blocks that compose the cameras.”

4. Line 157, I think the authors should write “NEF raw data” as readers might not know that this file format correspond to raw data.

Answer: You are absolutely right. We have changed the statement into “raw image data of the NEF format”, so it is more clear to the reader.

5. I am impressed by color differences in Figure 9, which highlights the importance of wide color spaces. In this case, waiting for more advanced color spaces in the future seems to be a good choice. Therefore, should raw data be the priority for cultural heritage conservation of images? Or is it necessary to choose only one color space?

Answer:  This question is related to questions 1 and 2. Therefore, they will all be answered here.

We are grateful for your comments and for expressing your concern in order to ensure the highest quality in this particular field of science and engineering. We are happy to clarify your doubts and we have expanded the manuscript accordingly. Raw image data consist of a digitalization of the light captured by the sensor of the camera in a numerical format that, while useful for storage and having the true captured data, it is neither designed nor suited for representation. Any image, 3D model or any other digital file type that concerns representation will not be able to read, no less display, raw image data without an internal process of transformation to RGB, which is exactly what we propose in this paper, with the added qualities that we enforce specific control so during that conversion from Raw to presentation-ready data, no valuable information is lost.

Therefore, answering to your concerns, it is sadly not possible to apply the captured Raw data for photogrammetry, but they can effectively be stored, so if, as you comment, bigger RGB spaces are invented, these data can be transformed into them. This way, Updated models with a bigger richness in hues can be made in the future.

We have added different paragraphs and sentences in the article explaining this thoroughly. Thank you again for your remarks.

6. Line 355, I think “y” should be “by”.

Answer: We are thankful to you for having noticed this typo. We fixed it.

7. Figure 12, the 3D model of the color checker seems rough but should be flat. How can an observer be sure that this phenomenon doesn’t occur on the 3D model of the object to conserve?

Answer: For the specific case of the color checker, problems are caused by the flat and uniformly coloured surfaces, on which no distinctive feature points are found. Many archaeological artifacts (such as the Etruscan mirrors presented as examples) exhibit rough and richly textured surfaces, on which these kinds of problems do not occur. For smooth and uniformly colored objects, as well as polished/shiny or transparent surfaces, photogrammetry is simply not an appropriate method.
A general method for evaluating the quality of a photogrammetric reconstruction is, for example, the re-projection error of estimated surface positions into camera image space, given the estimated camera parameters. However, this paper is concerned with color fidelity and not shape fidelity, such that these questions are can be left for future lines of research.

8. More generally, how can the 3D model fidelity be evaluated?

Answer: We are grateful for your concern, but this particular topic (overall 3D model fidelity) is outside the scope of this paper, which concerns itself thoroughly with colour integrity preservation. Nevertheless, this is the next step of the project this paper is framed in, so it is added as future lines of research, with its own dedicated publication based on the work published in this one.

9. Defects are present in the 3D models as explained by the authors. A proposed explanation is stitching defect and blending. I am not sure if it is linked to stitching as generally, stitching defects follow straight lines (corresponding to image border, potentially deformed) and this is not the case for the color checker. Also blending should normally homogenize colors. Could it be not a color problem, but 3D model artifacts based on incorrect evaluation of distance between the camera and the object surface by the software? Or is this distance provided by the user as input for the photogrammetry process?

It is true that 3D reconstruction errors are the underlying cause for the colour defects on the colour chart – consequently, wrong parts of the source images are associated with the surface points. The terms “blending” and “stitching” referred to the creation of the texture map – and as can be seen in Figure 4, the specific texture mapping algorithm used divides the surface in a multitude of small irregular patches

10. I really appreciate the four lighting settings (“Sun”, “Fluor”, “LED” and “Mixed”) in the experiments. This highlights the importance of the lighting conditions over the visual aspect and perception of an object. More explanations about the differences of lighting conditions when using a turntable should be added. With rotation of the object, light paths to the object are different in each image, which can have influence on the future registration during the photogrammetry process.

Thank you for pointing this out. It is very true that with rotating object, changing light paths can lead to different shadows, highlights, interreflections etc., which in turn cause problems in feature matching. This is a well-known issue in photogrammetry practice and in our setup we took precautions, such as using area lights (softboxes) to avoid hard shadows and the arrangement of the light sources symmetric to the camera axis for a uniform illumination and the avoidance of shadows altogether.

Unfortunately, the experiments described in this paper that use a turntable setup were only tested with one lighting situation (“Mixed”), while the others were imaged with the object stationary and the camera moving – thus, the different lighting setups cannot be evaluated with respect to feature matching performance.

In addition to this, as stated in answer 8, these aspects of photogrammetry are not really in the scope of this current paper, but can be addressed in future publications that can address the topic on a more holistic level.

11. Also, discussion on the most suitable lighting conditions for cultural heritage preservation can be interesting. This part is mainly discussed in the article from an “optimal workflow for photogrammetry” perspective but some objects are designed to interact with sunlight, sometimes at a given hour, such as some temples. In this case, should preserving the cultural heritage requires image acquisition in the lighting conditions expected by the designer or with artificial and control lighting conditions?

This is a very interesting and also a philosophical question. If we could know for certain that the creator of an artifact intended one specific lighting situation, then the imaging of an object under these conditions would be a valid option. However, especially for objects more mobile than a temple, the lighting intentions of their creators are hard to reconstruct and indeed the propositions that they were created with one specific lighting situation in mind is rather unlikely. The best that we can strive for is the capturing of the reflective properties of surfaces. Then on the contrary, rendering the objects under various lighting conditions can serve as a tool for archaeologists in investigating on the optimal lighting conditions for an object. This also contributes to the fact that various lighting sources can be used in the experimental set-up as a part to find the one that bears the best quality.

Added relevant text (in the conclusions):

“Future lines of research will ensure the guidelines on how to properly reproduce and respect other physical characteristics of the pieces, such as 3D details. Furthermore, an interesting aspect of the presented process is its scalability, and future improvements in colour reproduction technology are compatible with it. The acquired raw data can be transformed to any other existing RGB space, including wider spaces that most likely will be standardized in the future. This will allow updating already made models along time with newer technologies that can improve its quality and documentation experience.”

Round 2

Reviewer 3 Report

My comments have been addressed.