Image Quality Metrics, Personality Traits, and Subjective Evaluation of Indoor Environment Images
Round 1
Reviewer 1 Report
In the paper, an experimental study is described to investigate the relationship between the perceived quality of indoor environments, personality, and computational image quality metrics. Twelve image quality metrics were used to estimate participants’subjective evaluations. Ten-Item Personality Inventory (TIPI) is uesd to tested personality traits. Some interesting results were found about the image quality metrics, personality traits, and subjective evaluation of indoor environment images. Here, some points need to be addressed as detailed below before its publication.
1. This paper indicates that perceived colorfulness was highly correlated with perceived clarity and complexity. While according to the description of the visual experiment, the experimental sample is 40 participants. Is the sample data enough to support the results of the experiment?
2. In the results section, the author needs to explain that the purpose of calculating the P value is to test whether there is a significant difference between the mean values of the two populations, and what the different P values represent. In conclusion, more description is needed about the P value.
3. The content of the experimental results is not enough. Can the author provide more experimental phenomena, such as the distribution characteristics of indicators?
4. Some points concerning writing:
a) It is better to place periods and commas outside quotation marks in Line 76, 77.
b) When two articles are quoted at the same time, the quotation format is not uniform, such as [7-8], [23,24].
Author Response
We would like to thank the reviewer for the comments and feedback.
Comment 1: This paper indicates that perceived colorfulness was highly correlated with perceived clarity and complexity. While according to the description of the visual experiment, the experimental sample is 40 participants. Is the sample data enough to support the results of the experiment?
Response: We added the below explanation about our priori power analysis to determine sample size. “G*Power software [35] was used to determine the sample size needed for the experiment for an effect size of r = 0.40 (α = 0.05, 1−β = 0.80).”
Comment 2: In the results section, the author needs to explain that the purpose of calculating the P value is to test whether there is a significant difference between the mean values of the two populations, and what the different P values represent. In conclusion, more description is needed about the P value.
Response: We added a clarification for the P value in Results section. “To determine whether to reject the null hypothesis (there is no relationship between image quality metrics and subjective evaluations), p-values (p) are utilized in hypothesis testing. It is more likely to reject the null hypothesis with the smaller the p-value. The statistical significance threshold was considered p ≤0.05.”
Comment 3: The content of the experimental results is not enough. Can the author provide more experimental phenomena, such as the distribution characteristics of indicators?
Response: We are not sure what the reviewer means by “indicator” but Table 1 provides information on the distribution characteristics pf the image quality metrics assessed in this study. We also provided the raw data from the subjective evaluations of the images via an online repository (linked is provided in the data availability statement).
Comment 4: Some points concerning writing:
- a) It is better to place periods and commas outside quotation marks in Line 76, 77.
- b) When two articles are quoted at the same time, the quotation format is not uniform, such as [7-8], [23,24].
Response:
We placed periods and commas outside quotation and made the quotation format uniform.
Reviewer 2 Report
This topic is essential and contributes to the lighting system field.
However, these comments enhance the content, such as:
First, please write your affiliation if it exists.
Line 233: "It is reasonable to imagine that the image quality metrics can be utilized to estimate the perception of visual scenes to create a smart building system as shown in Fig. 1."
This statement is not necessary. In papers, please write the facts or hypotheses you want to prove. Please remove this statement and replace it to answer this question: what is reasonable / why it is necessary to estimate the perception of visual scenes to.....
Section: Introduction: too long,
I suggest dividing it into two other sections.
Introduction part (1.5~2 pages): you can include objectives, the significance of the work, related works, etc.
Another part (for example: the metrics of image quality, etc).
Table 2: How did you make the items ordered?
For example Row1: 1, 7, 3, 9, 5
col1: 1, 6
What does it mean?
Section3: Results,
Please avoid redundant data or repeating the information.
For example:
You presented Table3, and after that, you repeated the information. Please explain a little bit about what the number means or how it affects other parts in very simple words.
Remove the space 435 ~ 448
In Section: Discussion
You presented the section statistically, but remember your audience has general information, so please describe or present the meaning a little bit.
Conclusions: too short, please make some explanation or add more around one page. Please explain your results more.
Generally, the paper is good.
Author Response
We would like to thank the reviewer for the comments and feedback.
Comment 1:
Section: Introduction: too long,
I suggest dividing it into two other sections.
Introduction part (1.5~2 pages): you can include objectives, the significance of the work, related works, etc.
Another part (for example: the metrics of image quality, etc).
Response: The introduction is currently only two paragraphs. And the literature review is discussed under different subheadings (e.g., 1.1 Visual preference). Although the background studies are long, they are integral for the discussion of each parameter (e.g., colorfulness) since so much work has been done in four different areas.
Comment 2:
Table 2: How did you make the items ordered?
For example, Row1: 1, 7, 3, 9, 5
col1: 1, 6
What does it mean?
Response:
The items were ordered by the creator of Ten-Item Personality Inventory, as references in [33]. The column wise items represent the same personality type (e.g., items 1 and 5 denote extraversion). We added more explanation on the Ten-Item Personality Inventory scale to make this point clear.
Comment 3:
Section3: Results,
Please avoid redundant data or repeating the information.
For example:
You presented Table3, and after that, you repeated the information. Please explain a little bit about what the number means or how it affects other parts in very simple words.
Remove the space 435 ~ 448
Response:
We added a brief explanation to contextualize the results. The space was caused by our effort to put the table in the same page. After editing to the text, we can now remove the space.
Comment 4:
In Section: Discussion
You presented the section statistically, but remember your audience has general information, so please describe, or present the meaning a little bit.
Response:
We edited the discussion section to focus the implications of our findings, rather than the statistical results.
Comment 5:
Conclusions: too short, please make some explanation or add more around one page. Please explain your results more.
Response:
We expanded the conclusion section to further discuss the results, implications, and limitations.
Reviewer 3 Report
- i suggest to change "naive" in the abstract to participants without a domain-relevant background. naive has a negative connotation.
- Fig 1 is in part blurry, which might be an artistic effect that you want to achieve. However, it might be, that some of the information you want to transport ist lost.
- It would be interesting to provide the data of the images (all images) and their evaluation ratings by the probants.
Otherwise an interesting and inspiring paper.
Author Response
We would like to thank the reviewer for the comments and feedback.
Comment 1:
I suggest changing "naive" in the abstract to participants without a domain-relevant background. naive has a negative connotation.
Response:
In psychology research literature “naïve” is a term used for participants who do not know the purpose of the study (experimental research goals). However, we understand the term might have negative connotations for the general audience. Therefore, we changed all the "naive" to “participants without a domain-relevant background”
Comment 2:
Fig 1 is in part blurry, which might be an artistic effect that you want to achieve. However, it might be, that some of the information you want to transport ist lost.
Response:
Fig. 1 is a conceptual representation of the adaptive lighting system, and do not aim to provide specific visual information. We provided a little more information on the figure captions to make the conceptual diagram clearer.
Comment 3:
It would be interesting to provide the data of the images (all images) and their evaluation ratings by the probants. Otherwise an interesting and inspiring paper.
Response:
The link of these information was provided in the last sections before reference list:
“Data Availability Statement:
The raw data can be downloaded at: https://doi.org/10.6084/m9.figshare.21350214.v2”
