• ETRI Journal
• /
• v.25 no.3
• /
• pp.156-170
• /
• 2003

Gamut compression algorithms have traditionally been defined functionally and then tested with deductive methods, e.g., psychophysical experiments. Our study offers an alternative, an inductive method, in which observers judge image colors to represent the original images more accurately. We developed a computer-controlled interactive tool that modifies the color appearance of pictorial images displayed on a monitor. In experiments, observers used the tool to alter color pixels according to the region of color space to which they belonged. We created three different gamut compression algorithms based on the observer experimental data. Observer groups evaluated the performance of the newly-developed algorithms, existing gamut compression algorithms, and an image based on the average observers' results from experiments in this study. The study of gamut extension is unlike the study of gamut compression in that it mainly deals with the degree of image pleasantness as judged by observers. The results of the gamut extension experiments in this study not only make available worthwhile data but also suggest a methodology for using the observer experimental tool for future gamut extension research.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.49 no.4
• /
• pp.58-66
• /
• 2012

Currently many devices reproduce electronic images in the various ways. However, the color that is reproduced in any device is different from the original color due to the differences in the gamut between devices. A recent trend in gamut mapping algorithms is the use of spatial information to compute the color transformation of pixels from the input to the output gamut. However, these techniques share the problem of preserving details, and avoiding halos, and hue shift. In this paper, spatial gamut mapping for preserving the details of the input image is proposed. Our approach improves visibility of detail that is not effectively represented with conventional spatial gamut mapping. In proposed method, initially, we gamut map the input image using gamut clipping and obtain a detail layer for both the input and the gamut mapped images. Next, we calculate the difference between the two detail layers, obtaining the details of the out of gamut region. Finally, we add the details of out of gamut region to the gamut mapped image. Since the resulting image has out of gamut colors, we obtain resulting image of proposed method by using a gamut clipping method. Consequently, the printed output image was more consistent with the corresponding monitor image.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.42 no.2 s.302
• /
• pp.69-80
• /
• 2005

In these days, the technology development of the imaging/optic industry and the digital broadcasting replace the classic CRT with the new display devices that is getting slimmer and larger. Especially, when the general TV signal is applied directly to the wide gamut display using LED or laser, which can display higher chromatic colors that can't be reproduced on CRT, the color distortion occurs and it causes serious problems. Thus, in this paper the gamut mapping is studied, which gets rids of the color distortion and utilizes the wider color gamut than that of the CRT sufficiently. In the gamut mapping the general mapping concept is the increasement of the chroma on the same hue plane but it causes the over chromatic enhancement. So, the vector mapping, which increases the lightness md the chroma at the same time, is proposed to prevent the side effect. In the vector mapping the chromaticity is maintained constantly, hence the image can be seen more natural than that of the chroma mapping. By using the gamut fitting, it is compensated that the tone disappearance or the contour effect that is arose from the geometric properties of the input and the output color gamut. These gamut mapping and gamut fitting can prevent the color distortion and reproduce the natural image on the wide gamut displays.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.2
• /
• pp.1-10
• /
• 2004

This paper proposes the method that design CLUT(color look-up table) simultaneously processing gamut mapping and color space conversion using only CLUT without complex computation. After CLUT is constructed using scanner gamut and printer gamut, the scanner gamut is extended to include original scanner gamut. This extended scanner gamut is used as input CIE $L^{*}$ $a^{*}$ $b^{*}$ values for CLUT. Then CMY values are computed by using gamut mapping. Input RGB image of scanner is converted into CIE $L^{*}$ $a^{*}$ $b^{*}$ by using regression function. CIE $L^{*}$ $a^{*}$ $b^{*}$ values of scanner are converted into CMY values without computation of additional gamut mapping using the proposed CLUT. In the experiments, the proposed method resulted in the similar color difference, but reduced the complexity computation than the direct computing method to process gamut mapping and color space conversion respectively.espectively.ively.

• Proceedings of the Korean Printing Society Conference
• /
• 2000.12a
• /
• pp.0.3-0
• /
• 2000

Gamut mapping is a technique that acts on cross-media reproduction to transform a color between devices for the purpose of enhancing the appearance or preserving the appearance of an image. Gamut mapping essentially produces color conversion error which depends the gamut mapping method, source and destination devices, and sample points for gamut modeling. For color space conversion between monitor colors and printer colors, empirical representation using sample measurements is currently widely utilized. Color samples are uniformly selected in the device space such as CMY or RGB, represented as color patches, and then measured. However, in the case of printer, these color samples are not evenly distributed inside the printer gamut and the color conversion error is increased. Accordingly, this paper introduces a equally distributed color sampling method in CIELAB space, a device-independent color space, to reduce color conversion error, and the performance is analyzed via color space conversion experiments using tetrahedral interpolation.

• Proceedings of the IEEK Conference
• /
• 2003.07e
• /
• pp.1759-1762
• /
• 2003

This paper proposes the method that design CLUT(color look-up table) simultaneously processing gamut mapping and color space conversion using only LUT without complex computation. After we construct LUT composed of scanner gamut and printer gamut, we extend L$\^$*/a$\^$*/b$\^$*/ points based on input L$\^$*/a$\^$*/b$\^$*/ to include input scanner L$\^$*/a$\^$*/b$\^$*/ Input RGB image of scanner is converted into CIEL$\^$*/a$\^$*/b$\^$*/ using regression (unction. CIELAB values of scanner are convened into CMY values including gamut mapping processing without additional gamut mapping using the proposed CLUT. In the experiments, the proposed method resulted in the similar color difference, but reduced the complexity computation compared with processing gamut mapping and color space conversion respectively

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.01a
• /
• pp.80-84
• /
• 2009

This paper investigates the relationship between the compression ratio and the gamut area for a reconstructed image when using JPEG and JPEG2000. Eighteen color samples from the Macbeth ColorChecker are initially used to analyze the relationship between the compression ratio and the color bleeding phenomenon, i.e. the hue and chroma shifts in the a*b* color plane. In addition, twelve natural color images, divided into two groups depending on four color attributes, are also used to investigate the relationship between the compression ratio and the variation in the gamut area. For each image group, the gamut area for the reconstructed image shows an overall tendency to increase when increasing the compression ratio, similar to the experimental results with the Macbeth ColorChecker samples. However, with a high compression ratio, the gamut area decreases due to the mixture of adjacent colors, resulting in more grey.

• Journal of the Korean Graphic Arts Communication Society
• /
• v.19 no.2
• /
• pp.58-67
• /
• 2001

Gamut mapping is a technique that acts on cross-media color reproduction to transform a color between devices for the purpose of enhancing the appearance or preserving the appearance of an image. Gamut mapping essentially produces color conversion error which depends the gamut mapping method, source and destination devices, and sample points for gamut modeling. For color space conversion between monitor colors and printer colors, empirical representation using sample measurements is currently widely utilized. Color samples are uniformly selected in the device space such as CMY or RGB, represented as color patches, and then measured. However, in the case of printer, these color samples are not evenly distributed inside the printer gamut and the color conversion error is increased. Accordingly, this paper introduces a equally distributed color sampling method in CIELAB space, a device- independent color space, to reduce color conversion error, and the performance is analyzed via color space conversion experiments using tetrahedral interpolation.

• 한국정보디스플레이학회:학술대회논문집
• /
• 2009.10a
• /
• pp.1232-1235
• /
• 2009

Image compression techniques such as JPEG and MPEG induce losses of image quality. These losses are usually investigated on the spatial distortions from reconstructed images. Representative specifications are blocking artifacts, color bleeding and smearing. However, the compression techniques also influence the color information. The distortion of color information means distortion of gamut characteristics such as gamut size and unique color from the CIELAB values for each pixel in the reconstructed images. Accordingly, this paper introduces the investigation of the relationship between image compression and the gamut characteristics for reconstructed images using MPEG compression. The results show the consist variation of gamut, hue, and chroma due to MPEG compression.

• Proceedings of the IEEK Conference
• /
• 2003.07e
• /
• pp.1755-1758
• /
• 2003

색 재현 범위(Color Gamut)가 기존의 표준신호(예 sRGB, Rec. 709)대비 상이한 Laser 디스플레이 장치에서 Gamut Matching Algorithm을 이용하여 표준 컬러의 재현을 가능하게 하고, CRT 대비 광범위한 Laser Color Gamut 의 모든 색 영역을 표현 할 수 있다. 이 방법은 일정한 휘도 및 hue 에서 표준입력과 출력장치의 색 재현 범위에 따라 주어진 입력신호의 Chroma를 늘이거나, 줄임으로써 출력장치의 전 색 재현 범위를 사용할 수 있게 된다.