Frequently Asked Questions

• Does HDR-VDP-2 report differences in color?

No. However, color information is used to correctly compute photopic (daylight) and scotopic (night vision) luminance, i.e. Purkinje shift.

• Does HDR-VDP-2 work with ordinary (LDR) images?

Yes. You need to specify 'sRGB-display' as the color_encoding parameter and pass an RGB image in which the values range from 0 to 1. This color encoding assumes that the peak luminance of the display is 100 <math>cd/m^2</math>. Note that the matlab function imread will return a matrix of uint8 or unit16, which needs to be converted to the normalized floating point matrix: single(img)/2^8 or single(img)/2^16.

• <math>Q_{MOS}</math> predictions do not match my assessment of quality.

<math>Q_{MOS}</math> predictions were optimized for a range of distortions, including image compression, blocky artifacts, noise and blur. The full list can be found in the Calibration reports. This predictor is likely to be much less accurate for other type of distortions that were not considered. In such situation, the predictor <math>Q</math> could be a better choice.

• How to interpret the visibility predictions: <math>P_{det}</math> and <math>P_{map}</math> ?

<math>P_{det}</math> is probability of detecting a difference for the entire image assuming that each part of the image is equally attended; and <math>P_{map}</math> is a map (2D matrix) per-pixel probability. It should be interpreted as the probability of detection when an observer is focusing on a particular pixel.

For the current version of the C-HDR-VDP, <math>P_{det} = max(P_{map} )</math>. It was found that this choice gives the best match to psychophysical data and is also the most conservative estimate. Intuitively, if a hex pattern starts to be noticeable, it is detected in the part of the display where it is the most visible (hence the maximum function), regardless whether that part takes 90% or 10% of a display. In fact the probability of detection map already accounts for the higher visibility of larger areas (spatial integration).

The probabilities <math>P_{det}</math> and <math>P_{map}</math> are NOT the probabilities of the two-alternative-forced-choice (2AFC) experiment, in which the probability is affected by the chance of guessing the right answer. The probability <math>P_{det}</math> should be interpreted as the probability that an average observer correctly detects the difference while his or her chance of guessing is zero. For example an observer is presented a just noticeable pattern and a very large number (in fact infinite number) of flat luminance maps, from which he or she has to choose the one that contains the pattern. The <math>P_{det}</math> can vary from 0 to 1, while the probability in the 2AFC experiment is normally within the range from 0.5 to 1 because an observer has at least 0.5 chance of guessing right. The following paragraphs explain in detail the difference between <math>P_{det}</math> and the probabilities found in forced choice experiments.

The probability of a positive answer in a forced choice experiment is equal probability of detection (<math>P_d</math>) plus the probability of a chance (correct guess) conditional on the case when the pattern is not detected:

<math>P_p=P_d+(1-P_d){\cdot}P_c</math>.

From the above equation we get:

<math>P_d=\frac{P_p-P_c}{1-P_c}</math>.

In the two-alternative-choice experiment there is 50% chance of guessing the right answer (<math>P_c=0.5</math>). Therefore, in order to find the threshold for 50% probability of detection (<math>P_d=0.5</math>), the psychometric procedure is adjusted to converge at 75% probability of positive answer (<math>P_p=0.75</math>). Thus probability of detection <math>P_d</math>, which is equivalent to <math>P_{det}</math> in C-HDR-VDP, is different to the probability of giving correct answer in an 2AFC experiment.

This section is under construction.