practical scene illuminant estimation via flash/no-flash pairs

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Practical Scene Illuminant Estimation via Flash/No-Flash Pairs. Cheng Lu and Mark S. Drew Simon Fraser University {clu, mark} Flash/No-flash Imagery – a Brief History. diCarlo, Xiao, & Wandell, CIC 2001. Combine flash/no-flash images to produce a pure-flash image. - PowerPoint PPT Presentation


  • Practical Scene Illuminant Estimation via Flash/No-Flash PairsCheng Lu and Mark S. Drew Simon Fraser University{clu, mark}

  • This paper:Estimate Ambient Illuminant, usingFlash/No-flash Pairs

  • Whats the point?:Can estimate scene (ambient) illuminant without knowing: Flash SPD Camera sensors Surface reflectance

  • Why estimate the illuminant?White balance, plus many computer vision applications == intrinsic imageswithout illumination. Simple FastWhats good about this method?

  • The set-up:2 images , one under ambient lighting, & another under flash.Under Ambient: Image A.Under Both: Image B.

  • The Key: Pure-Flash ImageThe ambient light from A is also in B. Therefore if we subtract the two, we have F: the pure-flash image.

    Under Flash: Image F:

  • Incidentally, note that there are now extra shadows, from the flash(since its offset from the lens).Image F: the scene as imaged under Flash light only.

  • 1. Lambertian surface:RGB = Shading = normal effective light-directionIlluminantSurfaceSensors

  • 2. Narrow-band sensors:so thenis exactly a single-spike sensor:

  • 3. Planckian light:But, can violate 1., 2., 3. and still succeed.(in Wiens approximation)Gives

  • Now take Logs, to pull apart multiplications:Camera-dept vectorCamera-dept vectorIntensity and shadingSurfaceColor-temperature of lightwhere

  • Camera-dept vectorSurfaceColor-temperature of lightSo form geometric-mean chromaticity:Wed like to remove intensity/shading term:In logs:where

  • The point:As temp (light color) changes, move along straight line.But, we have A and F images: Subract them, and use same chromaticity trick Only illumination is left!

  • Log-difference Geometric-Mean ChromaticitySo log-log delivers inverse-temperature difference:Calibrate for 1/TA-1/TF, then in new scene obtain TA!{

  • What does thislook like?Moved to 2D; color-matching functions in geo-mean chromaticity. (9 Planckians, Macbeth ColorChecker, spike sensors, xenon flash SPD)

  • Sony DXC930 sensors, Daylights+F2, actual xenon flash SPD:Reference locusHow to proceed: Sharpen Find closest cluster

    mark - Sony already fairly sharp.

  • Effect of sharpening:Poor clustersBetter clusters#ingKodak DCS420:

  • Test: can we determine the illuminant?102 illuminants, Sony camera, Munsell patches102 illuminants, Sony camera, Macbeth patchesEstimate illum.from Munsell to Macbeth Nearly 100% correctly identified.

  • Application: White Balance4 calibration illuminants, HP camera, Macbeth chart(each cluster has 24 dots)No flash With flash Sharpen Sample image at 24 locationsevenly over imageSame (daylight) color balancefor training and for testingImage under CWF; CWF+Xenon

  • Overlaps best with CWF, so usewhite patch of Macbeth under CWF for white balance:Auto balance Wrong.Fluor balance Correct.Our color-balance Much closer.

  • Thanks!To Natural Sciences and Engineering Research Council of Canada