Adaptive height-modified histogram equalization and chroma correction in YCbCr color space for fast backlight image compensation

2011 ◽  
Vol 29 (8) ◽  
pp. 557-568 ◽  
Author(s):  
Bonghyup Kang ◽  
Changwon Jeon ◽  
David K. Han ◽  
Hanseok Ko
2014 ◽  
Vol 543-547 ◽  
pp. 2873-2878
Author(s):  
Hui Yong Li ◽  
Hong Xu Jiang ◽  
Ping Zhang ◽  
Han Qing Li ◽  
Qian Cao

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%.


2021 ◽  
Vol 7 (8) ◽  
pp. 150
Author(s):  
Kohei Inoue ◽  
Minyao Jiang ◽  
Kenji Hara

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.


2016 ◽  
Vol 2016 ◽  
pp. 1-17 ◽  
Author(s):  
Li Zhou ◽  
Du Yan Bi ◽  
Lin Yuan He

Foggy images taken in the bad weather inevitably suffer from contrast loss and color distortion. Existing defogging methods merely resort to digging out an accurate scene transmission in ignorance of their unpleasing distortion and high complexity. Different from previous works, we propose a simple but powerful method based on histogram equalization and the physical degradation model. By revising two constraints in a variational histogram equalization framework, the intensity component of a fog-free image can be estimated in HSI color space, since the airlight is inferred through a color attenuation prior in advance. To cut down the time consumption, a general variation filter is proposed to obtain a numerical solution from the revised framework. After getting the estimated intensity component, it is easy to infer the saturation component from the physical degradation model in saturation channel. Accordingly, the fog-free image can be restored with the estimated intensity and saturation components. In the end, the proposed method is tested on several foggy images and assessed by two no-reference indexes. Experimental results reveal that our method is relatively superior to three groups of relevant and state-of-the-art defogging methods.


2017 ◽  
Vol 24 (3) ◽  
pp. 406-415 ◽  
Author(s):  
Yoshiaki Ueda ◽  
Takanori Koga ◽  
Hideaki Misawa ◽  
Noriaki Suetake ◽  
Eiji Uchino

2001 ◽  
Vol 73 (3) ◽  
pp. 303-317 ◽  
Author(s):  
CICERO MOTA ◽  
JONAS GOMES ◽  
MARIA I. A. CAVALCANTE

We study the perceptual problem related to image quantization from an optimization point of view, using different metrics on the color space. A consequence of the results presented is that quantization using histogram equalization provides optimal perceptual results. This fact is well known and widely used but, to our knowledge, a proof has never appeared on the literature of image processing.


2013 ◽  
Vol 393 ◽  
pp. 556-560
Author(s):  
Nurul Fatiha Johan ◽  
Yasir Mohd Mustafah ◽  
Nahrul Khair Alang Md Rashid

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.


2019 ◽  
Vol 1367 ◽  
pp. 012028
Author(s):  
Bagaskara Aji Wicaksono ◽  
Ledya Novamizanti ◽  
Nur Ibrahim

2011 ◽  
Vol 121-126 ◽  
pp. 672-676 ◽  
Author(s):  
Xin Yan Cao ◽  
Hong Fei Liu

Skin color detection is a hot research of computer vision, pattern identification and human-computer interaction. Skin region is one of the most important features to detect the face and hand pictures. For detecting the skin images effectively, a skin color classification technique that employs Bayesian decision with color statistics data has been presented. In this paper, we have provided the description, comparison and evaluation results of popular methods for skin modeling and detection. A Bayesian approach to skin color classification was presented. The statistics of skin color distribution were obtained in YCbCr color space. Using the Bayes decision rule for minimum cot, the amount of false detection and false dismissal could be controlled by adjusting the threshold value. The results showed that this approach could effectively identify skin color pixels and provide good coverage of all human races, and this technique is capable of segmenting the hands and face quite effectively. The algorithm allows the flexibility of incorporating additional techniques to enhance the results.


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