A Real Time Color Gamut Mapping Method Using a Neural Network

2005 ◽  
pp. 328-331
Author(s):  
Hak-Sung Lee ◽  
Dongil Han
Keyword(s):  
Neural Network ◽  
Real Time ◽  
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 Relative Colorimetric Rending Mapping Method Based on BP Neural Network

2011 ◽  
Vol 55-57 ◽  
pp. 1830-1833
Author(s):  
Lei Zhao ◽  
Guang Xue Chen
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Network Theory ◽  
Mapping Method ◽  
Black Box ◽  
Gamut Mapping ◽  
Continuous Tone ◽  
Color Error ◽  
Neural Network Theory ◽  
Color Rendering

There are very complicated nonlinear relations between input value and presentation color of digital prepress devices, as well as in the gamut mapping among different devices. Not all the relations can be described by linear model properly. In recent years, neural network and black box theory are introduced to describe the relations. In this research, the printer gamut is divided into micro space sections, a relative colorimetric rending mapping method is proposed based on BP neural network theory to complete the gamut mapping from monitor gamut to color printer. Experimental results show that the model reduces the color error of color blocks between the two devices, and the color rendering method can be used for gamut mapping of image with less continuous tone.

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