Subjective contrast sensitivity function assessment in stereoscopic viewing of Gabor patches
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Rousson, Johanna
Haar, Jérémy
Platiša, Ljiljana
Piepers, Bastian
Kimpe, Tom R.
Philips, Wilfried
While 3D displays are entering hospitals, no study to-date has explored the impact of binocular disparity and 3D inclination on contrast sensitivity function (CSF) of humans. However, knowledge of the CSF is crucial to properly calibrate medical, especially diagnostic, displays. This study examined the impact of two parameters on the CSF: (1) the depth plane position (0 mm or 171 mm behind the display plane, respectively DP:0 or DP:171), and (2) the 3D inclination (0° or 45° around the horizontal axis of the considered DP), each of these for seven spatial frequencies ranging from 0.4 to 10 cycles per degree (cpd). The stimuli were computer-generated stereoscopic images of a vertically oriented 2D Gabor patch with a given frequency. They were displayed on a 24” full HD stereoscopic display using a patterned retarder. Nine human observers assessed the CSF in a 3-down 1-up staircase experiment. Medians of the measured contrast sensitivities and results of Friedman tests suggest that the 2D CSF as modeled by Barten1 still holds when a 3D display is used as a 2D visualization system (DP:0). However, the 3D CSF measured at DP:171 was found different from the 2D CSF at frequencies below 1 cpd and above 10 cpd. 
 Good afternoon, everybody. So I'm Joana Rousson and I would like to explain to you what I did during my studies, so entitled subjective contrast sensitivity function assessment in stereoscopic of gamma patches. But first of all, please let me introduce you and give you more insights about the context of the study. So as it was mentioned, I'm working on medical displays. So this study was intended for medical applications. So what you should know is medical displays and especially diagnostic displays, so for radiologists, needs to be calibrated. And why do they need to be calibrated? They need to be calibrated to ensure that whatever the device, a radiologist, or whatever the display the radiologist is using, we still have the same image representation. So wherever he is in the hospital or wherever he is in the world at another hospital using a diagnostic display, always the same image representation he should get. So how can we ensure consistent image representation? It's done by standardizing the displayed luminance to the luminance perceived by the eyes. And this is handled by accounting for the sensitivity of the human eye to changes in contrast. And this is also denoted as a CSF when we display a luminance. So the CSF stands for contrast sensitivity function. It's the human eye ability to detect a low contrast pattern stimulus. And it depends on the special frequency of that pattern. The contrast sensitivity function has been intensively studied since the 60s and it has even been modeled in the 90s, late 90s by Barton. Yet the contrast sensitivity function has always been studied under 2D visualization conditions only. And despite medical practice is progressively moving from 2D to 3D formats, no studies or almost non-studies have been performed to try to assess the contrast sensitivity function under 3D visualization conditions. So when looking at 3D images. So the objective of our study, I think as you can imagine, was to assess the 3D CSF. So would the CSF be different if we have a 3D display? If we look at the 3D display and 3D images, would the CSF be altered? We also wondered, okay, if we use a 3D display but under 2D visualization conditions, so as a normal 2D display, does the CSF still hold? That's also one of our questions during the study. And so we studied the CSF because we wanted to know if the calibration algorithms should be revised for medical displays. So methods and materials for this study. As equipment for our experiment, we use Barco 24-inch fully HD display. It comprised a pattern with order, so especially multiplexing the right and the left view. Okay, here is the stimuli we use. It's called a GABA patch. It's a 2D vertically oriented GABA patch. That's the system that we use during all the experiments. So the GABA patch is just, in fact, the multiplication of 2D cosine pattern with a dedicated frequency F and a dedicated contrast C in the formula. So you can see just here. And it's multiplied by a 2D Gaussian. So okay, for our experiment, we had also to add a few additional constants like A to account for the viewing distance and the pixel pitch because when we assess the CSF, we take care of having the proper visual angle, so in terms of visual degree, visual angle, we need to properly calibrate everything in terms of viewing distance, pixel pitch and so on to get the proper number. And also you have a few constants like the offset of the scaling that were used, in fact, to get digital driving levels. So instead of having numbers between 0, 1, having numbers between 0 and 255 that are required for the display. Okay, no, sorry. Yeah. So during these experiments, a few parameters were changed. So first the contrast. It's okay because with the CSF, to assess the CSF, the contrast sensitivity function, we need to find the contrast threshold. So the contrast at which the detector can barely see the stimulus or just can't see the stimulus anymore. So of course, we had to change the contrast to find this contrast threshold. Also the spatial frequency because as I mentioned, the contrast sensitivity function depends on the spatial frequency. But also to have what we call 3D visualization conditions, we altered the depth plane position. So the plane where the 2D Gabber patch was lying. And also we had some 3D inclination. So to explain it a bit more. So you have a Gabber patch. However, our Gabber patch was lying at the display plane. So that's what we call 2D visualization condition. Or we, let's say, moved our Gabber patch further from the observer. So kind of translation along the axis to have it lying at the depth plane, virtual depth or virtual plane that is behind the display plane. And then for the 3D inclination, what we did is just that we did a rotation around the x axis, around this axis, to create this 3D inclination. The 3D inclination was also only performed when we had a depth plane different from the display plane to ensure that the whole image was always behind the display plane. So we performed all the experiments for seven different special frequencies ranging from 0.4 cycles per degree to 10 cycles per degree. To the orientation, just to say that, OK, we studied a vertical Gabber patch, vertical oriented Gabber patch, no 2D orientation of a Gabber patch. Two 3D inclinations, so either 0 degree or 45 degree, and two depth plane, either 0 being the display plane or 171 millimeter behind the display plane. So in fact, we have three what we call configurations. So to assess the 2D CSF, it means that you have depth plane of 0 to inclination of 0. For the 3D CSF, you have depth plane different from the display plane and 3D inclination of 0. We also studied an overt 3D inclination. So for the subjective experiments, we used nine non-expert observers. They were all tested for their vision and for their sterocracy. We used a controlled environment to ensure that we had uniform psychophysical conditions over all the tests. Then we also, so to find the contrast threshold, we used a 3D 1-up staircase experiment. So the staircase, it consists into either decreasing or increasing the contrast of the displayed stimulus, depending on the response of the observer to the preceding stimulus. So if the observer said, yes, I see the stimulus, then we decrease the contrast by a certain step down. And if he says, no, I do not see the stimulus, then we increased the contrast by a certain step up. 3D 1-up, it stands for the fact that after the first reversal was reached, so the reversal is a change in the direction of the contrast. So after the first reversal is reached, three yes answers, so yes, three times the observer had to answer three times, yes, I see the stimulus to have a decrease in the contrast, while only a no answer was required to increase the contrast again. And so after we performed the staircase for 22 reversals, and the 22 reversals are reached, and then we used the last 20 reversals to make, so we took the mean and we determined the contrast threshold. And then you have to know that the contrast sensitivity is the inverse of contrast threshold. Okay, there were a little bit more calculation behind that that you can find in the paper, but in general that's how it's working. So for to analyze and all our data, so first we checked if it was normally distributed and it was not. So instead of this fun, this calculating and displaying means, we decided to go for medians and first and foremost quartiles and to go also for non-parametric significance testing, like for example the Freedman test, to compare medians of different configurations for different frequencies, but also the one sample Wecoxon sign-run test to compare in fact medians, the medians we measured for the 2DCSF to values written by Barton's model. So main results and conclusions for our study, when comparing our 3D, when using our 3D display as a 2D visualization device, so a depth plane of zero, so the display plane 3D inclination of zero, we wanted to know if we were still in agreement with Barton's model. So as you can see on this plot, but also in the results of the significance test, so one sample Wecoxon sign-run test, you can see that the null hypothesis is never rejected. So it would mean that there's no statistical significance proven between our measured medians and the value written by Barton. So what we drew as conclusion that okay, apparently according to this result, the 2DCSF still holds for 3D monitor when used as a 2D visualization device. Then this was, let's say, the more important part, it was to know if the 2DCSF differs or not from the 3DCSF. So 3DCSF, I remember you, it was when the depth plane behind the display plane only was considered, no 3D inclination yet. So what we, as you can notice, okay, on the plot, it seems that at low frequency there's a decrease in terms of contrast sensitivity, but a small increase at high frequencies. I remember that I put the medians first and third quartiles. And okay, the significance test, this thing, so comparing the medians for the 2DCSF to the medians measured for the 3DCSF, we see that at low frequencies and high frequencies, so below 1 cycle, till 1 cycle per degree and at 10 cycle per degree, the null hypothesis is rejected. So apparently there would be statistical difference between the 2D and the 3DCSF at these frequencies. So yeah, as you can notice. So okay, our results suggest that the 3DCSF would differ from the 2DCSF. Now let's compare. So here we are under 3D visualization conditions, but now let's add some 3D inclination. So instead of having no 3D inclination, now we have a 45 degree 3D inclination. Okay, if you look at the medians, we have the impression that there would be a decrease in sensitivity due to, no, it would be an increase in sensitivity thanks to the added 3D inclination, but in fact that was not confirmed by significance testing. And later we also did an over study with a 60 degree inclination and okay, maybe it was due to the observers, so we did that 60 degree inclination with new observers and we didn't have this tendency at all and also the null hypothesis was also rejected for all the frequencies. So apparently when adding a 3D inclination, we don't have an additional impact on the 3DCSF. So as conclusion, what we got from our study was that apparently the 2DCSF still holds for 3D monitors as a 2D monitor, but it seems that the 3DCSF differs from the 2DCSF. So if the 3DCSF differs from the 2DCSF, this means that maybe we should consider revising our calibration algorithm for 3D medical displays, but when displaying a 3D image, we can't calibrate it the same way when we add only 2D images. But okay, further studies are being performed on this topic to know exactly how it should be, how it should be altered and also run this experiment with more observers, but these were the first results we obtained. Okay, I would like to thank for that talk. IWT, who supported this project in the context of background ground named optical simulation modeling and evaluation of 3D medical displays and of course to give special thanks to all the observers who took part in the experiments. I thank you and if you want to see the stimulus, also the staircase and how it was built and also to see this depth plan, these 3D inclinations, we will be at the demo session. So this afternoon, this evening, and with all the equipment, okay, except the control room, but we will have all the software, the equipment, so if you want to have a look at this study, you are all invited to come and try it yourself being the observer yourself. Thank you. Thank you.
 Good afternoon, everybody.  So I'm Joana Rousson and I would like to explain to you what I did during my studies, so entitled  subjective contrast sensitivity function assessment in stereoscopic of gamma patches.  But first of all, please let me introduce you and give you more insights about the context  of the study.  So as it was mentioned, I'm working on medical displays.  So this study was intended for medical applications.  So what you should know is medical displays and especially diagnostic displays, so for  radiologists, needs to be calibrated.  And why do they need to be calibrated?  They need to be calibrated to ensure that whatever the device, a radiologist, or whatever  the display the radiologist is using, we still have the same image representation.  So wherever he is in the hospital or wherever he is in the world at another hospital using  a diagnostic display, always the same image representation he should get.  So how can we ensure consistent image representation?  It's done by standardizing the displayed luminance to the luminance perceived by the eyes.  And this is handled by accounting for the sensitivity of the human eye to changes in  contrast.  And this is also denoted as a CSF when we display a luminance.  So the CSF stands for contrast sensitivity function.  It's the human eye ability to detect a low contrast pattern stimulus.  And it depends on the special frequency of that pattern.  The contrast sensitivity function has been intensively studied since the 60s and it has  even been modeled in the 90s, late 90s by Barton.  Yet the contrast sensitivity function has always been studied under 2D visualization  conditions only.  And despite medical practice is progressively moving from 2D to 3D formats, no studies or  almost non-studies have been performed to try to assess the contrast sensitivity function  under 3D visualization conditions.  So when looking at 3D images.  So the objective of our study, I think as you can imagine, was to assess the 3D CSF.  So would the CSF be different if we have a 3D display?  If we look at the 3D display and 3D images, would the CSF be altered?  We also wondered, okay, if we use a 3D display but under 2D visualization conditions, so as  a normal 2D display, does the CSF still hold?  That's also one of our questions during the study.  And so we studied the CSF because we wanted to know if the calibration algorithms should  be revised for medical displays.  So methods and materials for this study.  As equipment for our experiment, we use Barco 24-inch fully HD display.  It comprised a pattern with order, so especially multiplexing the right and the left view.  Okay, here is the stimuli we use.  It's called a GABA patch.  It's a 2D vertically oriented GABA patch.  That's the system that we use during all the experiments.  So the GABA patch is just, in fact, the multiplication of 2D cosine pattern with a dedicated frequency  F and a dedicated contrast C in the formula.  So you can see just here.  And it's multiplied by a 2D Gaussian.  So okay, for our experiment, we had also to add a few additional constants like A to account  for the viewing distance and the pixel pitch because when we assess the CSF, we take care  of having the proper visual angle, so in terms of visual degree, visual angle, we need to  properly calibrate everything in terms of viewing distance, pixel pitch and so on to  get the proper number.  And also you have a few constants like the offset of the scaling that were used, in fact,  to get digital driving levels.  So instead of having numbers between 0, 1, having numbers between 0 and 255 that are  required for the display.  Okay, no, sorry.  Yeah.  So during these experiments, a few parameters were changed.  So first the contrast.  It's okay because with the CSF, to assess the CSF, the contrast sensitivity function,  we need to find the contrast threshold.  So the contrast at which the detector can barely see the stimulus or just can't see  the stimulus anymore.  So of course, we had to change the contrast to find this contrast threshold.  Also the spatial frequency because as I mentioned, the contrast sensitivity function depends  on the spatial frequency.  But also to have what we call 3D visualization conditions, we altered the depth plane position.  So the plane where the 2D Gabber patch was lying.  And also we had some 3D inclination.  So to explain it a bit more.  So you have a Gabber patch.  However, our Gabber patch was lying at the display plane.  So that's what we call 2D visualization condition.  Or we, let's say, moved our Gabber patch further from the observer.  So kind of translation along the axis to have it lying at the depth plane, virtual depth  or virtual plane that is behind the display plane.  And then for the 3D inclination, what we did is just that we did a rotation around the  x axis, around this axis, to create this 3D inclination.  The 3D inclination was also only performed when we had a depth plane different from the  display plane to ensure that the whole image was always behind the display plane.  So we performed all the experiments for seven different special frequencies ranging from  0.4 cycles per degree to 10 cycles per degree.  To the orientation, just to say that, OK, we studied a vertical Gabber patch, vertical  oriented Gabber patch, no 2D orientation of a Gabber patch.  Two 3D inclinations, so either 0 degree or 45 degree, and two depth plane, either 0 being  the display plane or 171 millimeter behind the display plane.  So in fact, we have three what we call configurations.  So to assess the 2D CSF, it means that you have depth plane of 0 to inclination of 0.  For the 3D CSF, you have depth plane different from the display plane and 3D inclination  of 0.  We also studied an overt 3D inclination.  So for the subjective experiments, we used nine non-expert observers.  They were all tested for their vision and for their sterocracy.  We used a controlled environment to ensure that we had uniform psychophysical conditions  over all the tests.  Then we also, so to find the contrast threshold, we used a 3D 1-up staircase experiment.  So the staircase, it consists into either decreasing or increasing the contrast of the  displayed stimulus, depending on the response of the observer to the preceding stimulus.  So if the observer said, yes, I see the stimulus, then we decrease the contrast by a certain  step down.  And if he says, no, I do not see the stimulus, then we increased the contrast by a certain  step up.  3D 1-up, it stands for the fact that after the first reversal was reached, so the reversal  is a change in the direction of the contrast.  So after the first reversal is reached, three yes answers, so yes, three times the observer  had to answer three times, yes, I see the stimulus to have a decrease in the contrast,  while only a no answer was required to increase the contrast again.  And so after we performed the staircase for 22 reversals, and the 22 reversals are reached,  and then we used the last 20 reversals to make, so we took the mean and we determined  the contrast threshold.  And then you have to know that the contrast sensitivity is the inverse of contrast threshold.  Okay, there were a little bit more calculation behind that that you can find in the paper,  but in general that's how it's working.  So for to analyze and all our data, so first we checked if it was normally distributed  and it was not.  So instead of this fun, this calculating and displaying means, we decided to go for medians  and first and foremost quartiles and to go also for non-parametric significance testing,  like for example the Freedman test, to compare medians of different configurations for different  frequencies, but also the one sample Wecoxon sign-run test to compare in fact medians,  the medians we measured for the 2DCSF to values written by Barton's model.  So main results and conclusions for our study, when comparing our 3D, when using our 3D display  as a 2D visualization device, so a depth plane of zero, so the display plane 3D inclination  of zero, we wanted to know if we were still in agreement with Barton's model.  So as you can see on this plot, but also in the results of the significance test, so one  sample Wecoxon sign-run test, you can see that the null hypothesis is never rejected.  So it would mean that there's no statistical significance proven between our measured medians  and the value written by Barton.  So what we drew as conclusion that okay, apparently according to this result, the 2DCSF still holds  for 3D monitor when used as a 2D visualization device.  Then this was, let's say, the more important part, it was to know if the 2DCSF differs  or not from the 3DCSF.  So 3DCSF, I remember you, it was when the depth plane behind the display plane only  was considered, no 3D inclination yet.  So what we, as you can notice, okay, on the plot, it seems that at low frequency there's  a decrease in terms of contrast sensitivity, but a small increase at high frequencies.  I remember that I put the medians first and third quartiles.  And okay, the significance test, this thing, so comparing the medians for the 2DCSF to  the medians measured for the 3DCSF, we see that at low frequencies and high frequencies,  so below 1 cycle, till 1 cycle per degree and at 10 cycle per degree, the null hypothesis  is rejected.  So apparently there would be statistical difference between the 2D and the 3DCSF at these frequencies.  So yeah, as you can notice.  So okay, our results suggest that the 3DCSF would differ from the 2DCSF.  Now let's compare.  So here we are under 3D visualization conditions, but now let's add some 3D inclination.  So instead of having no 3D inclination, now we have a 45 degree 3D inclination.  Okay, if you look at the medians, we have the impression that there would be a decrease  in sensitivity due to, no, it would be an increase in sensitivity thanks to the added  3D inclination, but in fact that was not confirmed by significance testing.  And later we also did an over study with a 60 degree inclination and okay, maybe it was  due to the observers, so we did that 60 degree inclination with new observers and we didn't  have this tendency at all and also the null hypothesis was also rejected for all the frequencies.  So apparently when adding a 3D inclination, we don't have an additional impact on the 3DCSF.  So as conclusion, what we got from our study was that apparently the 2DCSF still holds  for 3D monitors as a 2D monitor, but it seems that the 3DCSF differs from the 2DCSF.  So if the 3DCSF differs from the 2DCSF, this means that maybe we should consider revising  our calibration algorithm for 3D medical displays, but when displaying a 3D image, we can't calibrate  it the same way when we add only 2D images.  But okay, further studies are being performed on this topic to know exactly how it should  be, how it should be altered and also run this experiment with more observers, but these  were the first results we obtained.  Okay, I would like to thank for that talk.  IWT, who supported this project in the context of background ground named optical simulation  modeling and evaluation of 3D medical displays and of course to give special thanks to all  the observers who took part in the experiments.  I thank you and if you want to see the stimulus, also the staircase and how it was built and  also to see this depth plan, these 3D inclinations, we will be at the demo session.  So this afternoon, this evening, and with all the equipment, okay, except the control  room, but we will have all the software, the equipment, so if you want to have a look at  this study, you are all invited to come and try it yourself being the observer yourself.  Thank you.  Thank you.
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