An Improved Algorithm of Histogram Equalization to Increase Brightness of Image in Mine

2012 ◽  
Vol 204-208 ◽  
pp. 4789-4793
Author(s):  
Yan Bin Yuan ◽  
Bo Zhang ◽  
Xiao Hui Yuan ◽  
Xiao Pan Zhang ◽  
Wen Zhao Xia ◽  
...  
Keyword(s):  
Video Surveillance ◽  
Contrast Ratio ◽  
Histogram Equalization ◽  
Experimental Results ◽  
Equalization Algorithm ◽  
Improved Algorithm

To improve the contrast ratio and brightness of video surveillance image in mine, we modify the histogram equalization algorithm by extent the boundary when calculating the sum of gray probability. Experimental results show that the algorithm can reserve the characteristics of the histogram equalization and improve the image’s brightness.

scholarly journals A Stronger Aadaptive Local Dimming Method with Details Preservation

2020 ◽  
Vol 10 (5) ◽  
pp. 1820 ◽  
Author(s):  
Tao Zhang ◽  
Wenli Du ◽  
Hao Wang ◽  
Qin Zeng ◽  
Long Fan
Keyword(s):  
Subjective Evaluation ◽  
Contrast Ratio ◽  
Objective Evaluation ◽  
Histogram Equalization ◽  
Extraction Process ◽  
Extraction Algorithm ◽  
Equalization Algorithm ◽  
Retinex Theory ◽  
Local Dimming ◽  
Image Details

Local dimming technology focuses on improving the contrast ratio of the displayed images for a great visual perception. It consists of backlight extraction and pixel compensation. Considering a single existing backlight extraction algorithm can hardly adapt to images with diverse characteristics and rich details, we propose a stronger adaptive local dimming method with details preservation in this paper. This method, combining the advantages of some existing methods and introducing the combination of the subjective evaluation and the objective evaluation, obtains a stronger adaptation compared with others. Besides, to offset the luminance reduction caused in the backlight extraction process, we improve the bi-histogram equalization algorithm and propose a new pixel compensation method. To preserve image details, the Retinex theory is adopted to separate details. Experimental results demonstrate the effect of the proposed method on contrast ratio improvement and details preservation.

Design and Implementation of Spurs Detection System Based on OpenCV

2011 ◽  
Vol 345 ◽  
pp. 217-222
Author(s):  
Peng He ◽  
Lian Peng Wang ◽  
Na Wang ◽  
Gang Xu
Keyword(s):  
Computed Tomography ◽  
Embedded System ◽  
Detection System ◽  
Experimental Results ◽  
Design And Implementation ◽  
Function Expansion ◽  
The Embedded System ◽  
Improved Function ◽  
Small Bone ◽  
Improved Algorithm

In order to better solve the problem of detection of small bone spurs with convenient and accurate way, a portable spur detection system is designed. This system, in view of spur reproducibility characteristic, is characterized by the application for a kind of the improved algorithm based on the OpenCV. And it was successfully transplanted into the embedded system. The experimental results indicated that this system might precisely examine the small spur with difficulty discovery by naked eyes used fully by two images of computed tomography which done in different periods. The spur detection system needs to be further improved function to realize more applications. In fact, function expansion based on the system is easy to realize.

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 Illumination-robust face recognition based on deep convolutional neural networks architectures

2020 ◽  
Vol 18 (2) ◽  
pp. 1015
Author(s):  
Ridha Ilyas Bendjillali ◽  
Mohammed Beladgham ◽  
Khaled Merit ◽  
Abdelmalik Taleb-Ahmed
Keyword(s):  
Neural Networks ◽  
Face Recognition ◽  
Convolutional Neural Networks ◽  
Feature Learning ◽  
Histogram Equalization ◽  
Detection Algorithm ◽  
Deep Convolutional Neural Networks ◽  
Biometric Technology ◽  
Equalization Algorithm ◽  
Robust Face Recognition

<p><span>In the last decade, facial recognition techniques are considered the most important fields of research in biometric technology. In this research paper, we present a Face Recognition (FR) system divided into three steps: The Viola-Jones face detection algorithm, facial image enhancement using Modified Contrast Limited Adaptive Histogram Equalization algorithm (M-CLAHE), and feature learning for classification. For learning the features followed by classification we used VGG16, ResNet50 and Inception-v3 Convolutional Neural Networks (CNN) architectures for the proposed system. Our experimental work was performed on the Extended Yale B database and CMU PIE face database. Finally, the comparison with the other methods on both databases shows the robustness and effectiveness of the proposed approach. Where the Inception-v3 architecture has achieved a rate of 99, 44% and 99, 89% respectively.</span></p>

A Correction Algorithm of Multi-View Image System

2014 ◽  
Vol 631-632 ◽  
pp. 395-398
Author(s):  
Xin Yang Wang ◽  
Huan Xia Feng ◽  
Jian Zhang
Keyword(s):  
Light Source ◽  
Color Constancy ◽  
Histogram Equalization ◽  
Experimental Results ◽  
Image Correction ◽  
Correction Algorithm ◽  
Intrinsic Properties ◽  
Image System ◽  
Correction Effect ◽  
Color Restoration

This paper, based on the Retinex Color Constancy Theory, proposes a novel multi-view image correction algorithm, which correction effect is very effective. Histogram equalization,retinex processing and color restoration are performed for multi-view images,and extract reflectance which describe object intrinsic properties to eliminate un-consistent light source influence.The experimental results show that corrected images not only have high color contract,also have consistent color appearance with others.

Range limited adaptive brightness preserving multi-threshold histogram equalization algorithm

2017 ◽  
Vol 10 (6) ◽  
pp. 726-736
Author(s):  
许轰烈 XU Hong-lie ◽  
匡 程 KUANG Cheng ◽  
张 乐 ZHANG Le ◽  
李 莎 LI Sha ◽  
王树军 WANG Shu-jun ◽  
...  
Keyword(s):  
Histogram Equalization ◽  
Equalization Algorithm

scholarly journals Deep Colorization for Surveillance Images

2018 ◽  
Vol 228 ◽  
pp. 02009
Author(s):  
Chen Yao ◽  
Yan Xia
Keyword(s):  
Image Processing ◽  
Video Surveillance ◽  
Experimental Results ◽  
Grayscale Image ◽  
End To End ◽  
Surveillance Application

In video surveillance application, grayscale image often influences the image processing results. In order to solve the colorization problem for surveillance images, this paper propose a fully end-to-end approach to obtain a reasonable colorization results. A CNN learning structure and gradient prior are be used for chromatic space inferring. Finally, our experimental results show our advantage.

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