Wavelet Transform Adjustment Method Study in Color Image Enhancement

2014 ◽  
Vol 989-994 ◽  
pp. 3798-3801
Author(s):  
Zhi Gang Zhang ◽  
Shi Qiang Yan ◽  
Peng Geng
Keyword(s):  
Wavelet Transform ◽  
Image Enhancement ◽  
Basic Principle ◽  
Color Image ◽  
Experimental Result ◽  
Adjustment Method ◽  
Color Image Enhancement ◽  
Reflection Component ◽  
Enhancement Algorithm

In order to improve the ensemble of color image, this paper proposes homomorphism decomposition—wavelet enhancement algorithm based on the basic principle of Wavelet Transform. We separate the incidence component and reflection component of the image by homomorphism decomposition, and then combine wavelet transform to enhance image as well as reserve details. The experimental result shows that the adaption and effect is obviously superior to MSRCR.

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.

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.

scholarly journals A fast color image enhancement algorithm based on Max Intensity Channel

2014 ◽  
Vol 61 (6) ◽  
pp. 466-477 ◽  
Author(s):  
Wei Sun ◽  
Long Han ◽  
Baolong Guo ◽  
Wenyan Jia ◽  
Mingui Sun
Keyword(s):  
Image Enhancement ◽  
Color Image ◽  
Color Image Enhancement ◽  
Enhancement Algorithm
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