scholarly journals 2.4: Improving Picture‐reproducing Quality by a New Color Gamut Mapping Method

2021 ◽  
Vol 52 (S1) ◽  
pp. 16-19
Author(s):  
Daxue Xia ◽  
Lin Chen ◽  
Renli Xie
Keyword(s):  
Mapping Method ◽  
Color Gamut ◽  
Gamut Mapping

Study on Reproduction of Color Information of Digital Image Based on Different Color Gamut

2012 ◽  
Vol 430-432 ◽  
pp. 838-841
Author(s):  
Wen Ge Chen
Keyword(s):  
Image Processing ◽  
Digital Image ◽  
Color Space ◽  
Mapping Method ◽  
Color Information ◽  
Color Gamut ◽  
Gamut Mapping ◽  
Processing Software ◽  
Image Processing Software ◽  
Different Color

This paper is based on digital image color information reproduction error in a different color gamut,Through the different color gamut mapping method, image processing software Photoshop is used to make experiment and to obtain the corresponding image effect. Using digital presses to print out and use Spectrodensitometer measure the corresponding data.Using Excel software for data processing and analysis, digital image color information of loss situation is obtained in RGB and CMYK color space, It can provide certain basis for control of the color loss.

scholarly journals Hue-correction scheme considering CIEDE2000 for color-image enhancement including deep-learning-based algorithms

2020 ◽  
Vol 9 ◽  
Author(s):  
Yuma Kinoshita ◽  
Hitoshi Kiya
Keyword(s):  
Deep Learning ◽  
Image Enhancement ◽  
Color Image ◽  
Mapping Method ◽  
Experimental Results ◽  
Color Gamut ◽  
Gamut Mapping ◽  
Color Image Enhancement ◽  
Correction Scheme ◽  
Enhancement Algorithm

In this paper, we propose a novel hue-correction scheme for color-image-enhancement algorithms including deep-learning-based ones. Although hue-correction schemes for color-image enhancement have already been proposed, there are no schemes that can both perfectly remove perceptual hue-distortion on the basis of CIEDE2000 and be applicable to any image-enhancement algorithms. In contrast, the proposed scheme can perfectly remove hue distortion caused by any image-enhancement algorithm such as deep-learning-based ones on the basis of CIEDE2000. Furthermore, the use of a gamut-mapping method in the proposed scheme enables us to compress a color gamut into an output RGB color gamut, without hue changes. Experimental results show that the proposed scheme can completely correct hue distortion caused by image-enhancement algorithms while maintaining the performance of the algorithms and ensuring the color gamut of output images.

A testing paradigm for quantifying ICC profilers

2019 ◽  
Vol 2019 (1) ◽  
pp. 80-85
Author(s):  
Pooshpanjan Roy Biswas ◽  
Alessandro Beltrami ◽  
Joan Saez Gomez
Keyword(s):  
Digital Camera ◽  
Visual Assessment ◽  
Just Noticeable Difference ◽  
Color Management ◽  
Color Gamut ◽  
Gamut Mapping ◽  
Digital File ◽  
Mapping Process ◽  
Testing Paradigm

To reproduce colors in one system which differs from another system in terms of the color gamut, it is necessary to use a color gamut mapping process. This color gamut mapping is a method to translate a specific color from a medium (screen, digital camera, scanner, digital file, etc) into another system having a difference in gamut volume. There are different rendering intent options defined by the International Color Consortium [5] to use the different reproduction goals of the user [19]. Any rendering intent used to reproduce colors, includes profile engine decisions to do it, i.e. looking for color accuracy, vivid colors or pleasing reproduction of images. Using the same decisions on different profile engines, the final visual output can look different (more than one Just Noticeable Difference[16]) depending on the profile engine used and the color algorithms that they implement. Profile performance substantially depends on the profiler engine used to create them. Different profilers provide the user with varying levels of liberty to design a profile for their color management needs and preference. The motivation of this study is to rank the performance of various market leading profiler engines on the basis of different metrics designed specifically to report the performance of particular aspects of these profiles. The study helped us take valuable decisions regarding profile performance without any visual assessment to decide on the best profiler engine.

P‐13.11: A Color Gamut Mapping Reducing the Influence of IR‐drop in OLED Displays

2019 ◽  
Vol 50 (S1) ◽  
pp. 985-987
Author(s):  
Junting Ouyang ◽  
Bojia Lyu ◽  
DZ Peng ◽  
Kang Yang ◽  
Xiangzi Kong ◽  
...  
Keyword(s):  
Color Gamut ◽  
Gamut Mapping ◽  
Ir Drop

Gamut mapping method for ICC saturated intent

2007 ◽  
Author(s):  
Min-Ki Cho ◽  
Heui-Keun Choh ◽  
Se-Eun Kim ◽  
Yun-Tae Kim ◽  
Yousun Bang
Keyword(s):  
Mapping Method ◽  
Gamut Mapping

Three-Dimensional Color Gamut Visualization of Digital Output Device Based on ICC Profile

2012 ◽  
Vol 262 ◽  
pp. 36-39 ◽  
Author(s):  
Yun Hui Luo ◽  
Mao Hai Lin
Keyword(s):  
Dimensional Space ◽  
Color Space ◽  
Three Dimensional ◽  
Color Gamut ◽  
Digital Output ◽  
Gamut Mapping ◽  
Output Device ◽  
High Quality Image ◽  
Image Appearance ◽  
Cie Lab

As color gamut of digital output device greatly affects image appearance, accurate and effective gamut description for output device is intensively required for developing high-quality image reproduction technique based on gamut mapping. In this paper, we present a novel method to determine color gamut of output device by using a specific 3D reconstruction technology and device ICC profile. First, we populate the device color space by uniform sampling in the RGB 3-Dimensional space, and convert these sampling points to CMYK color space. Then, we work out the CIE LAB value of these points according to the ICC profile of output device. At last, in CIE LAB color space the boundary of these points is determined by using a gamut boundary descriptor based on Ball-Pivoting Algorithm (BPA) proposed by Bernardini. Compared with the results generated by ICC3D, our proposed method can compute device gamut more efficiently and at the same time give a more accurate gamut description of the output device. It will be help to develop effective gamut mapping algorithms for color reproduction.

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