Beyond Red&amp;#x2013;Green&amp;#x2013;Blue (RGB): Spectrum-Based Color Imaging Technology

Yamaguchi, Masahiro; Haneishi, Hideaki; Ohyama, Nagaaki

doi:10.2352/j.imagingsci.technol.(2008)52:1(010201)

Cited by 76 publications

(34 citation statements)

References 46 publications

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“…Figure 1 shows the experimental prototype system for multispectral and multiprimary video reproduction in the Natural Vision project [1]. As shown in this figure, not only the multispectral camera and display, but also interface, local encoder, and data format are needed to develop for practical use of multispectral imaging system.…”

Section: Introductionmentioning

confidence: 99%

“…They have been used not only for analysis applications, but also for reproducing the color of RGB images under a different illumination. The Natural Vision project [1] achieved a highly accurate color reproduction by estimating spectral reflectance from a multispectral image even under different illumination environment. This highly accurate color reproduction is expected to apply to a visual communication system for telediagnosis and home care, digital archives, and electronic commerce application such as online shopping.…”

Section: Introductionmentioning

confidence: 99%

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Multispectral information hiding in RGB image using bit-plane-based watermarking and its application

Shinoda

Watanabe

Hasegawa

et al. 2015

Opt Rev

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Although it was expected that multispectral images would be implemented in many applications, such as remote sensing and medical imaging, their use has not been widely diffused in these fields. The development of a compact multispectral camera and display will be needed for practical use, but the format compatibility between multispectral and RGB images is also important for reducing the introduction cost and having high usability. We propose a method of embedding the spectral information into an RGB image by watermarking. The RGB image is calculated from the multispectral image, and then, the original multispectral image is estimated from the RGB image using Wiener estimation. The residual data between the original and the estimated multispectral image are compressed and embedded in the lower bit planes of the RGB image. The experimental results show that, as compared with Wiener estimation, the proposed method leads to more than a 10 dB gain in the peak signal-to-noise ratio of the reconstructed multispectral image, while there are almost no significant perceptual differences in the watermarked RGB image.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multispectral information hiding in RGB image using bit-plane-based watermarking and its application

Shinoda

Watanabe

Hasegawa

et al. 2015

Opt Rev

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“…[1][2][3][4][5] In these methods, the colors of objects are accurately obtained by multiband imaging technologies, and the images are reproduced on displays with high color fidelity based on adequate calibration procedures for display systems. However, it is physically impossible to accurately reproduce the luster of objects, because luster usually has a significant luminance.…”

Section: Introductionmentioning

confidence: 99%

Fidelity evaluation of metallic luster in six-band high-dynamic-range imaging

Murakami

Jin

Manabu

et al. 2012

OPT REV

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This paper presents subjective evaluation results for images reproducing metallic luster. The images were produced by a six-band high-dynamic-range imaging technique, which provides high color fidelity and the capability of various tone mapping operations. The preferences for images produced by four kinds of tone mapping operations were evaluated by means of a paired comparison method under the conditions that observers could or could not refer to real scenes. The evaluation results indicated that preferences for images depend on tone mapping operations, especially for objects that have the luster changing over a large area with moderately high intensity. In addition, when referring to a real scene, the spatially varying tone compression, which reproduces the color and complex characteristics of metallic luster, was significantly preferable to the tone mappings by other approaches. Without a real scene, the preference was also strong for images produced by simply saturating pixel values at highlights. #

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“…The analysis of space resolved spectral information is only possible to a certain limit with an ordinary colour camera [1], [2]. The technical function principle of ordinary Red Green Blue (RGB) cameras with a maximum of three colour channels can dissolve only a limited range in the colour space and loose spectral image information.…”

Section: Introductionmentioning

confidence: 99%

Multispectral Image Correction for Geometric Measurements

Rosenberger

Linß

2015

J. Phys.: Conf. Ser.

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Abstract. Multispectral-and hyperspectral imaging technologies enable new possibilities in industrial measurement applications. Based on the knowledge of remote sensing a lot of investigations were made in the last decades of years. Nevertheless the demands on remote sensing versus technical multi spectral image processing are quite different. In the field of precise geometric measurement technics it is necessary to correct the image data between different spectral channels with a high accuracy, normally in the micron range. Otherwise the geometric absolute value of fail detection on edges can be become very large. State of the art in industrial imaging and detection of geometric features is the calibration of only one imaging channel. In this paper, the studies on a twelve channel multi spectral imager were presented. For the applied filter wheel system, investigations on the improvement of lens aberration as well as for the defocus problem were made. Therefore a calibrated high precision geometric test chart was used to calibrate the system geometrically. To correct the geometric errors on the image plane a special moving filter approach, based on linear convolution, was developed. For every channel a calibration matrix were calculated and applied on the image system output.

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Beyond Red–Green–Blue (RGB): Spectrum-Based Color Imaging Technology

Cited by 76 publications

References 46 publications

Multispectral information hiding in RGB image using bit-plane-based watermarking and its application

Multispectral information hiding in RGB image using bit-plane-based watermarking and its application

Fidelity evaluation of metallic luster in six-band high-dynamic-range imaging

Multispectral Image Correction for Geometric Measurements

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