Camerabased projector calibration, investigation of the Bala method

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Camerabased projector calibration, investigation
of the Bala method

• Espen Bårdsnes Mikalsen
• The Norwegian Color Research Laboratory
• Faculty of Computer Science and Media Technology
• Gjøvik University College, Gjøvik, Norway
• ebmikalsen_at_hotmail.com, http//www.colorlab.no,
• Supervisors Jon Yngve Hardeberg and
  Jean-Baptiste Thomas
• Master thesis presentations, Gjøvik, 07.06.2007

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Outline

• Introduction
• Implementing the Bala method
• Experimental setup
• Results
• Conclusion

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• The Bala method
• Calibration method for projectors presented by
  Raja Bala and Karen Braun, Xerox co, 2006.
• Focuses on tone response calibration, no 3 x 3
  transform matrix.
• Using a digital photo camera as a luminance
  measurement device by calibrating camera through
  visual luminance matching. Using the calibrated
  camera to tone response calibrate projector.

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• Research questions
• Q1 Verification of the Bala method
• An evaluation of the calibration method
  suggested by Bala and Braun. Implementation and
  performance testing with a final numeric results
  and analysis as a measure of performance.
  Separate evaluation of methods parts to identify
  strengths and weaknesses in the approach.
• Q2 Extensions to the Bala method
• In the original paper where the calibration
  method was presented the authors purposed some
  extensions that could increase the methods
  performance. Through implemetation and analysis
  these will be evaluated. Extensions are visual
  matching of three luminance values per estimated
  curve instead of one, and separate correction of
  R, G and B color channel replacing uniform
  luminance correction.

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• Simple walkthrough of the Bala method
• Step 1 - gather information
• Step 2 - process information to estimate
  projector tone response and correction curve

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• Step 1 - Visual matching of luminance
• A binary rasterpattern consisting of 50 black
  and 50 white pixels. Adjust the background
  colors luminance to perceptually match binary
  pattern. The adjusted luminance of background is
  the perceptually found 50 luminance value.

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• Display calibration target
• Luminance patch chart ranging from min to max
  luminance, with horizontal and vertical
  duplications of matched 50 luminance for use
  with non-uniformity correction.

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• Step 1 Capture image
• Capture an image of the projected chart with the
  uncalibrated camera.

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• Step 2 Retrive data from captured image
• Rotate and crop image

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• Step 2 Retrive data from captured image
• Read RGB data from image. Gives 24 individual
  sets of RGB.
• RGB sets are converted to a luminance value for
  each patch.

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• Step 2 Perform non-uniformity correction
• Devices like cameras and projectors often suffer
  from some kind of spatial non-uniformity.
  Non-uniformity is when a device responds
  spatially non-uniform to a uniform input. When
  capturing an image of a projection, the image
  will suffer from both non-uniformity of projector
  and of camera.
• This method does not correct for non-uniformity
  in projection, but corrects for non-uniformity in
  data used for calibration of camera and
  projector.
• Correction are based on calculating differances
  between the spread out duplications of the 50
  luminance patch.

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• Step 2 Estimating camera tone response curve
• Knowing the relationship between projected
  luminances and target luminances ( min, max and
  50 ) makes it possible to interpolate an
  estimation of the cameras tone response curve.

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• Step 2 - Example of estimated camera TRC

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• Extensions to original method
• Instead of only determining camera TRC based on
  the 50 luminance point. Add two new luminances (
  25 and 75 ) to help determine curve.
• Instead of using same correction curve for R, G
  and B channel. Estimate curves separatly.

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• Experiment setup
• Projectors
• Projectiondesign ActionOne DLP, 2003 model
• Panasonic AX-100 LCD, 2006 model
• Cameras
• Nikon D200 DSLR
• FujiFilm s7000 compact digital camera
• Spectroradiometer
• Minolta
• Room conditions
• Dark room, only luminance from projection

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• Results Visual matching
• Experiment set up to determine if visually
  matched luminance values deviate from person to
  person and when repeating matching of same value.
  Matching done at 3 luminance levels for R, G, B
  and gray channel.
• 6 observers visually matching 12 luminances 3
  times. A total of 216 values were matched.

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• Results - non-uniformity correction

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• Results Camera TRC estimation (ActionOne -
  Nikon)

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• Results Camera TRC estimation (Panasonic -
  Nikon)

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• Results Camera TRC estimation (ActionOne -
  Nikon)

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• Results Estimated projector TRC (ActionOne -
  Nikon)

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• Results Estimated projector TRC (Panasonic -
  Nikon)

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• Results Correction w/ correction curve
  (ActionOne-Nikon)

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• Results Correction w/ separate RGB correction
  curves (ActionOne-Nikon)

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• Results Correction w/ correction curve
  (ActionOne-Nikon)

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• Conclusion
• Q1 Verification of the Bala method
• It has to some extent been proven that
  calibration of projectors using this method will
  result in a more exact reproduction of color then
  for example using standard sRGB gamma correction.
  Correction results are better for DLP then LCD
  projector, probably because of LCD conforms
  better to the sRGB gamma curve, and correction
  will therefore be less necessary.
• Q2 Extensions to the Bala method
• It has been proven that interpolating camera TRC
  with not only one visually matched point, but
  several will improve accuracy of camera TRC, and
  therefore also estimated projection TRC and
  correction curve. If retrieving separate camera
  TRC for R, G and B color channel has a positive
  effect on method performance has not yet been
  proven.