Embedded Signal Processing Laboratory,
Wireless Networking and Communications Group,
The University of Texas at Austin,
Austin, TX 78712 USA
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Paper Draft - PowerPoint Slides - PDF Slides - Software Release
Related Resources: ESPL-LIVE HDR Image Database - Crowdsourced HDR IQA Study - No Reference HDR IQA Methods - PhD Dissertation on HDR IQA
Answer: Although we only used correlation-based IQA measures in this paper, we compute root mean squared error (RMSE) RMSE values and reduced chi-squared test of subjective ratings vs. predicted ratings in follow-up papers on HDR image quality assessment:
Question #2: How could you better handle noise in measurements and uncertainty in correlation coefficients?
Answer: This paper uses two previous subjective evaluation studies of 20 participants for tonempapping operators [Yeganeh & Wang, 2013] and 27 participants for compression [Narwaria, Da Silva, Le Callet & Pepion, 2013]. With a smaller number of opinion scores, there can be a wider variability in the ability of an automated algorithm to predict subjective results. After we had submitted our ICIP 2016 paper in January 2016, we collaborated with Alan Bovik and Deepti Ghadiyaram here at UT Austin to compile the ESPL-LIVE HDR database with over 1800 HDR images and obtain over 300,000 opinion scores from more than 5000 participants in a crowdsourced study using Amazon Mechanical Turk. Each HDR image has at least 40 evaluations.
Question #3: How did you choose the parameters in the proposed naturalness measure?
Answer: We used the parameters from [Yeganeh & Wang, 2013] as is. We could have followed the approach in the [Yeganeh & Wang paper and trained the parameters on a large set of natural images to determine the parameters in the naturalness measure.
Question #4: What is the range of values for the proposed quality measure?
Answer: The minimum value is 0. The maximum value is slightly greater than 1 due to the betadelta1 term where delta1 is 0.7088. The parameter beta is the exponent of the fit to a generalized Gaussian density of the mean subtracted contrast normalized pixels of the tonemapped image. For natural images, beta can be greater than 1; in fact, beta commonly takes values between 0.8 and 1.4.
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Last Updated 10/01/16.