scholarly journals Image Enhancement of Underwater Digital Images by Utilizing L*A*B* Color Space on Gradient and CLAHE based Smoothing

2016 ◽  
Vol 4 (9) ◽  
pp. 22-30 ◽  
Author(s):  
Ramandeep Kaur ◽  
Dipen Saini
Keyword(s):  
Image Enhancement ◽  
Digital Images ◽  
Color Space

Underwater Image Enhancement Method Combining color and Luminance

2020 ◽  
Vol 13 ◽  
Author(s):  
ZHAO Baiting ◽  
WANG Feng ◽  
JIA Xiaofen ◽  
GUO Yongcun ◽  
WANG Chengjun
Keyword(s):  
Image Enhancement ◽  
Color Space ◽  
Low Frequency ◽  
Brightness Enhancement ◽  
Color Distortion ◽  
Underwater Image ◽  
Enhancement Method ◽  
Frequency Components ◽  
Image Contour ◽  
Objective Indicators

Background:: Aiming at the problems of color distortion, low clarity and poor visibility of underwater image caused by complex underwater environment, a wavelet fusion method UIPWF for underwater image enhancement is proposed. Methods:: First of all, an improved NCB color balance method is designed to identify and cut the abnormal pixels, and balance the color of R, G and B channels by affine transformation. Then, the color correction map is converted to CIELab color space, and the L component is equalized with contrast limited adaptive histogram to obtain the brightness enhancement map. Finally, different fusion rules are designed for low-frequency and high-frequency components, the pixel level wavelet fusion of color balance image and brightness enhancement image is realized to improve the edge detail contrast on the basis of protecting the underwater image contour. Results:: The experiments demonstrate that compared with the existing underwater image processing methods, UIPWF is highly effective in the underwater image enhancement task, improves the objective indicators greatly, and produces visually pleasing enhancement images with clear edges and reasonable color information. Conclusion:: The UIPWF method can effectively mitigate the color distortion, improve the clarity and contrast, which is applicable for underwater image enhancement in different environments.

scholarly journals Underwater Image Enhancement via Medium Transmission-Guided Multi-Color Space Embedding

2021 ◽  
pp. 1-1
Author(s):  
Chongyi Li ◽  
Saeed Anwar ◽  
Junhui Hou ◽  
Runmin Cong ◽  
Chunle Guo ◽  
...  
Keyword(s):  
Image Enhancement ◽  
Color Space ◽  
Underwater Image

scholarly journals A Low-Light Sensor Image Enhancement Algorithm Based on HSI Color Model

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3583 ◽  
Author(s):  
Shiping Ma ◽  
Hongqiang Ma ◽  
Yuelei Xu ◽  
Shuai Li ◽  
Chao Lv ◽  
...  
Keyword(s):  
Image Enhancement ◽  
Color Space ◽  
Color Model ◽  
Low Light ◽  
Image Brightness ◽  
Low Contrast ◽  
Light Sensor ◽  
Hsi Color Model ◽  
Art Research ◽  
Enhancement Algorithm

Images captured by sensors in unpleasant environment like low illumination condition are usually degraded, which means low visibility, low brightness, and low contrast. In order to improve this kind of images, in this paper, a low-light sensor image enhancement algorithm based on HSI color model is proposed. At first, we propose a dataset generation method based on the Retinex model to overcome the shortage of sample data. Then, the original low-light image is transformed from RGB to HSI color space. The segmentation exponential method is used to process the saturation (S) and the specially designed Deep Convolutional Neural Network is applied to enhance the intensity component (I). At the end, we back into the original RGB space to get the final improved image. Experimental results show that the proposed algorithm not only enhances the image brightness and contrast significantly, but also avoids color distortion and over-enhancement in comparison with some other state-of-the-art research papers. So, it effectively improves the quality of sensor images.

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 Improving Discrimination in Color Vision Deficiency by Image Re-Coloring

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2250 ◽  
Author(s):  
Huei-Yung Lin ◽  
Li-Qi Chen ◽  
Min-Liang Wang
Keyword(s):  
Image Enhancement ◽  
Color Vision ◽  
Subjective Evaluation ◽  
Color Space ◽  
Natural Images ◽  
Natural Scene ◽  
Color Vision Deficiency ◽  
Color Separation ◽  
Color Deficiency ◽  
Natural Scene Images

People with color vision deficiency (CVD) cannot observe the colorful world due to the damage of color reception nerves. In this work, we present an image enhancement approach to assist colorblind people to identify the colors they are not able to distinguish naturally. An image re-coloring algorithm based on eigenvector processing is proposed for robust color separation under color deficiency transformation. It is shown that the eigenvector of color vision deficiency is distorted by an angle in the λ , Y-B, R-G color space. The experimental results show that our approach is useful for the recognition and separation of the CVD confusing colors in natural scene images. Compared to the existing techniques, our results of natural images with CVD simulation work very well in terms of RMS, HDR-VDP-2 and an IRB-approved human test. Both the objective comparison with previous works and the subjective evaluation on human tests validate the effectiveness of the proposed method.

Joint HIS Color Space Based Image Enhancement under Uneven Illumination

2013 ◽  
Vol 718-720 ◽  
pp. 2232-2236
Author(s):  
Rui Xu Guo ◽  
Le Tian Zhang
Keyword(s):  
Image Processing ◽  
Image Enhancement ◽  
High Performance ◽  
Color Space ◽  
Histogram Equalization ◽  
Homomorphic Filtering ◽  
Novel Algorithm

In this paper, we present a novel algorithm for uneven illumination image processing based on HIS color space and joint color space. Compared with many existing algorithms of image enhancement for the uneven illumination image, the proposed method have high performance compared with Histogram Equalization, Homomorphic filtering and Retinex. Some experiments are implemented to testify this conclusion.

The Research of the Digital Image-Processing of Colorful Painting

2014 ◽  
Vol 926-930 ◽  
pp. 3709-3712
Author(s):  
Yun Zhan ◽  
Jie Lei
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Digital Images ◽  
Color Space ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Practical Application ◽  
Digital Image Processing Technique ◽  
Basic Concepts

The research of the digital image-processing of colorful painting is mainly to aim at the objective circumstances between the digital image and drawing flat vision distortion. This paper is based on the basic concepts of the digital image-processing technique. It expounds digital images advantage, collect, characteristics, recognition and the choice of the color space, the practical application of the digital image in the painting area in sequence. Through the study, we found computer has powerful ability to analyze management in the colorful painting field.

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