Efficient and simple methods for display tone‐response characterization

Bala, Raja; Klassen, R. Victor; Braun, Karen M.

doi:10.1889/1.2812997

Cited by 7 publications

(5 citation statements)

References 11 publications

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“…Several sources assume that the offset is about 2% of the maximum luminance projected per channel [3,4,31,34]. We thus simulate this by adding 2% of luminance per channel.…”

Section: Simulation Of a Multi-projector Systemmentioning

confidence: 99%

Seam-Based Edge Blending for Multi-Projection Systems

Pedersen¹,

Suazo²,

Thomas³

2016

IJSIP

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“…Several sources assume that the offset is about 2% of the maximum luminance projected per channel [3,4,31,34]. We thus simulate this by adding 2% of luminance per channel.…”

Section: Simulation Of a Multi-projector Systemmentioning

confidence: 99%

Seam-Based Edge Blending for Multi-Projection Systems

Pedersen¹,

Suazo²,

Thomas³

2016

IJSIP

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“…6,[19][20][21] Recently, a method to retrieve the response curve of a projection display using an uncalibrated camera has been proposed. 20,22,23 The second step of these models is commonly the use of a 3 × 3 matrix containing primary chromaticities to build the colorimetric transform from luminance to an additive reference color space such as XYZ. The primary chromaticities can be generic primaries such as sRGB 24 for some applications, 22,23 data supplied by the manufacturer, 6 or can be estimated by measurement of the device primaries at full intensity, using a colorimeter or a spectroradiometer, assuming their chromaticity constancy.…”

Section: Modeling Displaysmentioning

confidence: 99%

High‐end colorimetric display characterization using an adaptive training set

Colantoni¹,

Thomas²,

Hardeberg³

2011

J Soc Info Display

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International audienceA new, accurate, and technology-independent display color-characterization model, and its application to the colorimetric rendering of multispectral images, 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 ΔEab* unit or below for several displays. The maximum error is shown to be low as well

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“…Thereafter, the tristimulus values, CIEXYZ or CIELAB, are estimated through a linear transformation using a matrix. [3][4][5][6][7] After the conversion process from a device dependent color space to device independent color space, color data from two devices can be mapped using gamut mapping algorithms based on compression and clipping methods. The goal of gamut mapping is improved color reproduction, which needs to be evaluated by the human eye without reference.…”

Section: Introductionmentioning

confidence: 99%

User-Configured Monitor-to-Printer Color Reproduction

Jang¹,

Kyung²,

Ha³

et al. 2011

jist

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Every type of color imaging device has its own color reproduction method, providing color characteristic information. Thus, a color management system with an ICC profile is generally used to reproduce colors between two different color imaging devices, for example, from a monitor to a printer. However, once the ICC profile of a device is measured and stored, it usually remains unchanged. Yet, a user can sometimes control the monitor configuration, such as the color temperature, contrast, and brightness, according to their preference, thereby changing the color characteristics of the monitor. In addition, typical end user's viewing condition is not matched to standard environment. In this case, if the user then prints an image on the monitor screen, the color of the printed image will not match the color displayed on the monitor screen, as the color characteristics of the ICC profile provided by the monitor manufacturer will no longer represent the user-configured color characteristics of the monitor. Therefore, this article proposes a method for user-configured monitor-to-printer color reproduction based on an estimation of the monitor characteristics under user's monitor configuration and viewing condition. First, the color characteristics according to change of monitor configuration is measured and modeled for the red-green-blue (RGB) chromaticity and tone curve. Second, to estimate the color characteristics of the user's monitor, color matching between a printed color chart and a reproduced color chart image on the monitor screen by soft proofing is accomplished. The RGB chromaticity and tone curve models are used in a soft proofing process for adjusting the monitor's color characteristics. After color matching, color characteristics of the user's monitor are then obtained. Finally, the monitor to printer color reproduction is evaluated based on the color characteristics obtained for the monitor. Experimental results using the proposed method show that the printed images have almost the same colors as the images on the real user-configured monitor screen.

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Efficient and simple methods for display tone‐response characterization

Cited by 7 publications

References 11 publications

Seam-Based Edge Blending for Multi-Projection Systems

Seam-Based Edge Blending for Multi-Projection Systems

High‐end colorimetric display characterization using an adaptive training set

User-Configured Monitor-to-Printer Color Reproduction

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