Hi, On the topic of alternatives to reflective charts for profiling cameras, how about taking a photograph of the solar spectrum through a spectroscope? You can use the positions of the absorption lines to register your image against the well-known solar spectrum and then compare your image data against the expected intensity of each color. I think the image at the end of this page would be characteristic of what you'd get: http://www.ifa.hawaii.edu/~hodapp/solar-spectroscope-1.html Does this image look like it would provide valuable data? Can you hack together a spectroscope of sufficient quality with some razor blades and a diffraction grating, without the machine shop? Andrew On Wed, Mar 11, 2009 at 4:15 PM, Graeme Gill <graeme@xxxxxxxxxxxxx> wrote: > howdy555@xxxxxxxxx wrote: > >> 1) Is there any option that would increase the profile quality even >> more than -qu? With -qm I get peak err = 2.808569, avg err = 0.511902, >> with -qu: peak err = 1.891550, avg err = 0.446999, so maybe with -qX >> (as in eXtreme) I would get 1.50? :). The calculation time with a LUT >> profile is very reasonable, even for the 'ultra' quality. > > It's not clear exactly what your workflow is, or where these > numbers come from. Are they from colprof ? How many points > are in your test set ? > As has been noted, the self fit errors do not give much > real indication of how accurate a profile, you need independent > measurements for this. You may well find that the self fit numbers > get worse as you increase the number of test points used (since the > profile will be unable to track the noise), even though the accuracy > of the profile is increasing. > > Generally average errors < 1.0 indicate that you are either fitting > a very small number of points, or are close to the repeatability > limits of the device/instrument. > >> The original implementation makes a weighted average of 2 XYZ values read: >> the "fast" one (with a very small integration time) and the "slow" one > > Actually, the current 1.0.3 release code does something different, > it does an initial very short reading, and then uses that to scale the > real reading. I prefer that because it minimized quantization, but > unfortunately the Spyder3 doesn't cope with the short measurement > and plays up, hence the change to an incremental scheme. > >> - possibly increasing the integration time, with the increase being the >> weight). This puzzled me as the average is very far from the source of >> all the errors - the meter's sensors. > > Since the sensor readings and XYZ are linearly related (the > "level 2" correction doing nothing typically for the Spyder 3), > I'm not sure this makes any difference in itself. > >> Therefore I tried a different approach: >> I averaged the sensor readings and THEN calculated XYZ from the >> averaged data. The real novelty however is that I allowed ONLY >> non-zero sensor values into the average. So each sensor "k" has its own >> "n[k]" and its own "accumulatedValue[k]" (with the result equal to >> sensor[k] = accumulatedValue[k]/n[k], of course). This makes the >> problem of "zero XYZ result for non-zero sensor values" much less >> likely to occur. To get better results, I averaged 4 readings: fast one, >> moderately slow one and 2 very slow ones. > > It's hard to know what's going on in the instrument. The sensors have > a typical dark frequency of 0.3 Hz, so should produce at least two > transitions > in 5 seconds when not illuminated, but this doesn't seem to be the > case. It does seem reasonable to work at the sensor reading level > if zero sensor readings are to be detected. > >> speed: it is much slower than the original method although I would say >> it is usable even for monitor calibration. Any further increase in >> integration time or number of averaged measurements seems to be >> unacceptable for this purpose though. > > I may have more of a play with it, and determine how long the integration > time needs to be on my instrument to guarantee non-zero sensor readings. > >> 3) The camera calibration - this one puzzles me so I would really be >> grateful for some insights about my wacky idea: >> >> Why can't I use my trashy monitor as a calibration target? Why do I >> have to use expensive calibration targets? If I understand correctly > > Pretty much, yes. The reason is that the spectral output shape of > a monitor is narrow band, since this is the best way of achieving > a wide color gamut with minimal cost (ie. 3 colorants). The real world > colors of reflective objects typically the subject of most photography > have the opposite characteristic of a smoother, broadband spectrum. > A reflective measurement chart is therefore much more characteristic > of what the camera is going to be used on, while the spectral > interaction between a monitor and camera sensor is likely to > be relatively unpredictable in its correlation to the real world. > > You could do something like what you are suggesting, and create > a profile, but much like using a scanner in place of an instrument, > you might be disappointed with the result. > > Graeme Gill. > >