Spectral Color Reproduction Using an Interim Connection Space-Based Lookup Table

Tsutsumi, Shohei; Rosen, Mitchell R.; Berns, Roy S.

doi:10.2352/j.imagingsci.technol.(2008)52:4(040201)

Cited by 6 publications

(5 citation statements)

References 17 publications

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“…designed a spectral acquisition and modeling system, specifically for works of art. The most promising approaches to spectral reproduction are based on higher-dimensional interim connection spaces Tsutsumi et al 2008]. However, as pointed out by Morovič et al [2012], the major limit on the quality of spectral reproduction is the spectral gamut of a 2D printer, which is significantly smaller than the naturally occurring spectral gamut.…”

Section: Previous Workmentioning

confidence: 99%

Deep multispectral painting reproduction via multi-layer, custom-ink printing

Shi¹,

Babaei

Kim³

et al. 2018

ACM Trans. Graph.

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We propose a workflow for spectral reproduction of paintings, which captures a painting's spectral color, invariant to illumination, and reproduces it using multi-material 3D printing. We take advantage of the current 3D printers' capabilities of combining highly concentrated inks with a large number of layers, to expand the spectral gamut of a set of inks. We use a data-driven method to both predict the spectrum of a printed ink stack and optimize for the stack layout that best matches a target spectrum. This bidirectional mapping is modeled using a pair of neural networks, which are optimized through a problem-specific multi-objective loss function. Our loss function helps find the best possible ink layout resulting in the balance between spectral reproduction and colorimetric accuracy under a multitude of illuminants. In addition, we introduce a novel spectral vector error diffusion algorithm based on combining color contoning and halftoning, which simultaneously solves the layout discretization and color quantization problems, accurately and efficiently. Our workflow outperforms the state-of-the-art models for spectral prediction and layout optimization. We demonstrate reproduction of a number of real paintings and historically important pigments using our prototype implementation that uses 10 custom inks with varying spectra and a resin-based 3D printer.

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Section: Previous Workmentioning

confidence: 99%

Deep multispectral painting reproduction via multi-layer, custom-ink printing

Shi¹,

Babaei

Kim³

et al. 2018

ACM Trans. Graph.

View full text Add to dashboard Cite

show abstract

“…where v i are eigenvectors in the metameric black spectrum P (I, P) and N p are the eigenvectors of the PQR values. Spectral gamut mapping is necessary in the spectral color reproduction process because a solution must be delivered for all spectral requests, even those outside of the printer's spectral gamut [14]. Because the resulting CIELAB is within the colorimetric gamut of the printer, it is only necessary to consider mapping the input sample in the PQR gamut.…”

Section: Methodsmentioning

confidence: 99%

Charamer mismatch-based spectral gamut mapping

Wu¹

2019

Laser Phys. Lett.

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This paper proposes a new spectral gamut mapping framework based on a subspace clustering strategy. Using a node address array-based lookup table, the scheme applies an initial partitioning of the spectral color space of a device into several subspaces with high degrees of correlation between spectral characteristics to enable the construction of point clusters. The Wyszecki hypothesis is then applied to break the spectrum of each point cluster into a fundamental spectrum and a metameric black spectrum, which are both converted to a LabPQR space in which the conventional 6D spatial mapping problem is simplified to 3D mapping within the PQR gamut. Experimental results indicate that the proposed framework improves the effectiveness of spectral gamut mapping by reducing the spectral artificial error while enhancing spatial visualization.

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“…In addition, LabPQR have effectively gamut boundary and gamut mapping algorithms [11]. It had reported that LabPQR could be used successfully in several applications [12,13]. However, these ICSs have obvious illuminants dependence property.…”

Section: Introductionmentioning

confidence: 99%

Weighted LabPQR Interim Connection Space Based on Human Color Vision for Spectral Color Reproduction

Liu

Yang

et al. 2014

Journal of Spectroscopy

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A weighted LabPQR interim connection space, based on human color vision, is proposed for retaining more visual color information. A new weight function proposed in our paper is connected with color-matching function and then further weighted the PQR dimensions of LabPQR compared with the other two weight functions and nonweight function. The results indicated that weighting obviously improved the colorimetric representing accuracy and robustness compared with nonweighting, and the new weight function outperformed the other two weight functions. The weighted LabPQR of the new weight function is most suitable for spectral color reproduction.

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Spectral Color Reproduction Using an Interim Connection Space-Based Lookup Table

Cited by 6 publications

References 17 publications

Deep multispectral painting reproduction via multi-layer, custom-ink printing

Deep multispectral painting reproduction via multi-layer, custom-ink printing

Charamer mismatch-based spectral gamut mapping

Weighted LabPQR Interim Connection Space Based on Human Color Vision for Spectral Color Reproduction

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