Color image enhancement technique using gamut mapping based on color space division

2003 ◽  
Author(s):  
Yang-Ho Cho ◽  
Yun-Tae Kim ◽  
Ho-Keun Lee ◽  
Yeong-Ho Ha
Keyword(s):  
Image Enhancement ◽  
Color Image ◽  
Color Space ◽  
Enhancement Technique ◽  
Gamut Mapping ◽  
Space Division ◽  
Color Image Enhancement

scholarly journals Hue-Preserving Saturation Improvement in RGB Color Cube

2021 ◽  
Vol 7 (8) ◽  
pp. 150
Author(s):  
Kohei Inoue ◽  
Minyao Jiang ◽  
Kenji Hara
Keyword(s):  
Image Enhancement ◽  
Color Image ◽  
Color Space ◽  
Histogram Equalization ◽  
Experimental Results ◽  
Color Image Enhancement ◽  
Histogram Specification ◽  
Target Intensity ◽  
Rgb Color Space ◽  
Intensity Image

This paper proposes a method for improving saturation in the context of hue-preserving color image enhancement. The proposed method handles colors in an RGB color space, which has the form of a cube, and enhances the contrast of a given image by histogram manipulation, such as histogram equalization and histogram specification, of the intensity image. Then, the color corresponding to a target intensity is determined in a hue-preserving manner, where a gamut problem should be taken into account. We first project any color onto a surface in the RGB color space, which bisects the RGB color cube, to increase the saturation without a gamut problem. Then, we adjust the intensity of the saturation-enhanced color to the target intensity given by the histogram manipulation. The experimental results demonstrate that the proposed method achieves higher saturation than that given by related methods for hue-preserving color image enhancement.

scholarly journals Color Systems and Color Image Enhancement Methods

1970 ◽  
Vol 10 (2) ◽  
pp. 97-110
Author(s):  
Akira Taguchi
Keyword(s):  
Image Enhancement ◽  
Color Image ◽  
Color Space ◽  
Histogram Equalization ◽  
Color Image Processing ◽  
Saturation Intensity ◽  
Color Image Enhancement ◽  
Color System ◽  
Hsi Color Space ◽  
Rgb Color Space

There are many color systems. Some systems are correspond to the human visual system, such as the Munsell color system. Other systems are formulated to ease data processing in machines, such as RGB color space. At first, Munsell color system is introduced in this paper. Next, RGB color system and hue-saturation-intensity (HSI) color system which is derived from RGB color systems are reviewed. HSI color system is important, because HSI color system is closely related to Munsell color system. We introduce the advantage and drawbacks of the conventional HSI color space. Furthermore, the improved HSI color system is introduced. The second half of this paper, we introduce a lot of color image enhancement methods based on the histogram equalization or the differential histogram equalization. Since hue preserving is necessary for color image processing, intensity processing methods by using both intensity and saturation in HSI color space are reviewed. Finally, hue preserving color image enhancement methods in RGB color system are explained.

Color Image Enhancement on YIQ Color Space

2014 ◽  
Vol 631-632 ◽  
pp. 478-481
Author(s):  
Feng Xiao ◽  
Shui Qing Miao ◽  
Li Guo
Keyword(s):  
Image Enhancement ◽  
Color Image ◽  
Color Space ◽  
Histogram Equalization ◽  
Color Images ◽  
Experimental Results ◽  
Color Image Enhancement ◽  
True Color Image ◽  
Rgb Color Space ◽  
True Color

The three components of the color images enhance the images directly in the RGB color space, will cause distortion of the image. So our paper will convert true color image from RGB space to YIQ space, the holomorphic filtering and histogram equalization are executed on Y component to make the image enhancement, the Y component contains a lot of image information; finally, the image is converted from YIQ color space to RGB color space once again. Experimental results show that the approach which were proposed in the paper, Combined with the method of holomorphic filtering and histogram equalization to overcome the uneven illumination, the image is dark and other shortcomings to achieve satisfactory enhancement.

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.

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