0000000000302632

AUTHOR

Philippe Colantoni

showing 4 related works from this author

Sampling CIELAB color space with perceptual metrics

2016

International audience

[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV][INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV][ INFO.INFO-TI ] Computer Science [cs]/Image ProcessingComputingMilieux_MISCELLANEOUS
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On the uniform sampling of CIELAB color space and the number of discernible colors

2013

This paper presents a useful algorithmic strategy to sample uniformly the CIELAB color space based on close packed hexagonal grid. This sampling scheme has been used successfully in different research works from computational color science to color image processing. The main objective of this paper is to demonstrate the relevance and the accuracy of the hexagonal grid sampling method applied to the CIELAB color space. The second objective of this paper is to show that the number of color samples computed depends on the application and on the color gamut boundary considered. As demonstration, we use this sampling to support a discussion on the number of discernible colors related to a JND.

Color histogram[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONcomputational color imagingColor balance[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologyperceptually uniform color spaceColor space01 natural sciences010309 optics[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingICC profile0103 physical sciencesColor depth[ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineering3D close packed hexagonal gridComputer visionSamplingComputingMilieux_MISCELLANEOUS[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingComputingMethodologies_COMPUTERGRAPHICSMathematicsColor differencebusiness.industry020207 software engineeringColor quantizationColor modelArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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High-end colorimetric display characterization using an adaptive training set

2011

A new, accurate, and technology-independent display color-characterization model is introduced. It is based on polyharmonic spline interpolation and on an optimized adaptive training data set. The establishment of this model is fully automatic and requires only a few minutes, making it efficient in a practical situation. The experimental results are very good for both the forward and inverse models. Typically, the proposed model yields an average model prediction error of about 1 ∆Eab* unit or below for several displays. The maximum error is shown to be low as well. freedom given to the model considering the choice of a tar- get color space and of the kernel and smoothing factor for the int…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingColor spaceColor management01 natural scienceslaw.invention010309 opticsPolyharmonic spline[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processinglaw0103 physical sciences0202 electrical engineering electronic engineering information engineeringComputer visionElectrical and Electronic EngineeringComputingMethodologies_COMPUTERGRAPHICSbusiness.industryColor correctionAtomic and Molecular Physics and OpticsElectronic Optical and Magnetic MaterialsKernel (image processing)RGB color model020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingSmoothingInterpolation
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A geometrical approach for inverting display color-characterization models

2008

— Some display color-characterization models are not easily inverted. This work proposes ways to build geometrical inverse models given any forward color-characterization model. The main contribution is to propose and analyze several methods to optimize the 3-D geometrical structure of an inverse color-characterization model directly based on the forward model. Both the amount of data and their distribution in color space is especially focused on. Several optimization criteria, related either to an evaluation data set or to the geometrical structure itself, are considered. A practical case with several display devices, combining the different methods proposed in the article, are considered …

Structure (mathematical logic)Mathematical optimizationComputer scienceInverseColor spaceAtomic and Molecular Physics and OpticsElectronic Optical and Magnetic MaterialsDisplay deviceCharacterization (materials science)Set (abstract data type)Distribution (mathematics)Electrical and Electronic EngineeringAlgorithmInterpolationJournal of the Society for Information Display
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