Quadrant dynamic clipped histogram equalization with gamma correction for color image enhancement

2020 ◽  
Vol 45 (4) ◽  
pp. 644-655 ◽  
Author(s):  
Bharath Subramani ◽  
Magudeeswaran Veluchamy
Keyword(s):  
Image Enhancement ◽  
Color Image ◽  
Histogram Equalization ◽  
Gamma Correction ◽  
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.

An Improved Color Image Enhancement Algorithm Based on 3-D Color Histogram Equalization

2013 ◽  
Vol 321-324 ◽  
pp. 1133-1137
Author(s):  
Yu Ting Song ◽  
Xiu Hua Ji ◽  
Shi Lin Zhao
Keyword(s):  
Image Enhancement ◽  
Color Image ◽  
Histogram Equalization ◽  
Color Images ◽  
Color Histogram ◽  
Test Results ◽  
Gray Scale ◽  
Color Image Enhancement ◽  
Equalization Algorithm ◽  
Enhancement Algorithm

This paper proposes an improved color image enhancement algorithm based on 3-D color histogram equalization algorithm. When the existed 3-D color histogram equalization algorithms in the literatures are applied in processing dim color images, the processed color images often turn pale due to the decrease of color-saturations and have false contours due to gray-scale merging phenomenon in the histogram equalization algorithm. In this paper, the proposed algorithm can make more pixels of the processed color images keep their color-saturations and reduce the gray-scale merging with Logarithmic histogram equalization algorithm. Test results with dim color images present a better effect of image enhancement.

Several Color Image Enhancement Method Comparison

2013 ◽  
Vol 380-384 ◽  
pp. 3770-3773
Author(s):  
Ting Ting Huang ◽  
Yuan Li ◽  
Zhen Xiang Xie
Keyword(s):  
Image Enhancement ◽  
Color Image ◽  
Method Comparison ◽  
Objective Evaluation ◽  
Histogram Equalization ◽  
Color Images ◽  
Simulation Experiments ◽  
Analysis Process ◽  
Color Image Enhancement ◽  
Enhancement Method

In this paper, the image analysis process, based on the characteristics of color images, were used histogram equalization, homomorphism filtering, Retinex multistage optimization and Zadeh-X transform for image processing, the use of simulation experiments, compared several methods in the image enhancement application, experimental results are presented and compared using several methods of objective evaluation.

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