Aerial Image Enhancement based on YCbCr Color Space

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.

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

IEEE Transactions on Image Processing ◽

10.1109/tip.2021.3076367 ◽

2021 ◽

pp. 1-1

Author(s):

Chongyi Li ◽

Saeed Anwar ◽

Junhui Hou ◽

Runmin Cong ◽

Chunle Guo ◽

...

Keyword(s):

Image Enhancement ◽

Color Space ◽

Underwater Image

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Efficient RGB to YCbCr Color Space Conversion for Embedded Application

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.543-547.2873 ◽

2014 ◽

Vol 543-547 ◽

pp. 2873-2878

Author(s):

Hui Yong Li ◽

Hong Xu Jiang ◽

Ping Zhang ◽

Han Qing Li ◽

Qian Cao

Keyword(s):

Direct Method ◽

Color Space ◽

Video Data ◽

Floating Point ◽

Portable Devices ◽

Embedded Processor ◽

Color Space Conversion ◽

Ycbcr Color Space ◽

Original Approach ◽

General Method

Modern embedded portable devices usually have to deal with large amounts of video data. Due to massive floating-point multiplications, the color space conversion is inefficient on the embedded processor. Considering the characteristics of RGB to YCbCr color space conversion, this paper proposed a strategy for truncated-based LUT Multiplier (T-LUT Multiplier). On this base, an original approach converting RGB to YCbCr is presented which employs the T-LUT Multiplier and the pipeline-based adder. Experimental results demonstrate that the proposed method can obtain maximum operating frequency of 358MHz, 3.5 times faster than the direct method. Furthermore, the power consumption is less than that of the general method approximately by 15%~27%.

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

Sensors ◽

10.3390/s18103583 ◽

2018 ◽

Vol 18 (10) ◽

pp. 3583 ◽

Cited By ~ 8

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.

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Hue-Preserving Saturation Improvement in RGB Color Cube

Journal of Imaging ◽

10.3390/jimaging7080150 ◽

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.

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Gray image colorization in YCbCr color space

2012 1st International Conference on Emerging Technology Trends in Electronics, Communication & Networking ◽

10.1109/et2ecn.2012.6470101 ◽

2012 ◽

Cited By ~ 1

Author(s):

Smriti Kumar ◽

Ayush Swarnkar

Keyword(s):

Color Space ◽

Image Colorization ◽

Gray Image ◽

Ycbcr Color Space

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Human Body Parts Detection Using YCbCr Color Space

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.393.556 ◽

2013 ◽

Vol 393 ◽

pp. 556-560

Author(s):

Nurul Fatiha Johan ◽

Yasir Mohd Mustafah ◽

Nahrul Khair Alang Md Rashid

Keyword(s):

Human Body ◽

Skin Color ◽

Color Space ◽

Detection Algorithm ◽

Color Segmentation ◽

Color Model ◽

Body Parts ◽

Color Spaces ◽

Morphological Operation ◽

Ycbcr Color Space

Skin color is proved to be very useful technique for human body parts detection. The detection of human body parts using skin color has gained so much attention by many researchers in various applications especially in person tracking, search and rescue. In this paper, we propose a method for detecting human body parts using YCbCr color spaces in color images. The image captured in RGB format will be transformed into YCbCr color space. This color model will be converted to binary image by using color thresholding which contains the candidate human body parts like face and hands. The detection algorithm uses skin color segmentation and morphological operation.

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Improving Discrimination in Color Vision Deficiency by Image Re-Coloring

Sensors ◽

10.3390/s19102250 ◽

2019 ◽

Vol 19 (10) ◽

pp. 2250 ◽

Cited By ~ 8

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.

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