检索结果-内蒙古大学图书馆

Research on a DS-class X-ray film digitisation device and an image enhancement algorithm with 12-bit RAW data

INSIGHT 2023年第6期65卷 313-318页

作者： Lv, Zhigang Li, Liangliang Wang, Peng Wang, Hongxi Li, Xiaoyan Xian Technol Univ Sch Mechatron Engn Xian Peoples R China Xian Technol Univ Sch Elect & Informat Engn Xian Peoples R China

Automatic evaluation of the X-ray films of welds is an important area of study in the field of non-destructive testing (NDT). A digitising device for the X-ray film is the key to realising automatic evaluation and its image quality directly determines the quality of the automatic evaluation system. At present, the imaging quality of most mature digitising systems on the market cannot meet the DS- class requirements of international standard EN 14096. In order to solve the problems of low visual contrast, detailed information that is difficult to distinguish and low visual resolution in existing digitising systems, a high-quality embedded X-ray film digitising device, processing films with adjustable width, is developed in this paper. The device uses a 12-bit camera and has the characteristics of small size, simple operation and easy maintenance. In order to improve the imaging quality, an optical visual enhancement model is constructed for the generated 12-bit RAW data, which can improve the display of the data. The MTF20% values of the device in the horizontal and vertical directions are 7.544 and 7.460, respectively, and the optical density range is 0.5-4.5 D, the comprehensive index of which can reach DS class. The device has been initially applied by non-destructive testing companies.

关键词： DS-class requirement EN 14096 12-bit RAW data standard reference film image enhancement algorithm

来源：评论

学校读者我要写书评

暂无评论

Efficient image enhancement algorithm for images of steel reinforcing bars in concrete obtained by a new solid-state sensor-based system

引用

IET SCIENCE MEASUREMENT & TECHNOLOGY 2007年第5期1卷 255-260页

作者： Benitez, D. S. Quek, S. Gaydecki, P. Univ Manchester Sch Elect & Elect Engn Sensing Imaging & Signal Proc Grp Manchester M60 1QD Lancs England

This work describes a new image-processing method capable of enhancing the raw images of steel reinforcing bars in concrete obtained by a new generation of imaging instrument based on solid-state magneto-inductive (MI) sensors. The new method considers the non-uniform response of the static search coil and addresses the problem of image blurring because of the field distribution pattern and bar depth. Experimental results obtained for different steel bar specimens are presented showing a significant enhancement of the original image information regarding bar mesh position and contrast.

关键词： image blur Distribution patterns Concrete search coil image enhancement algorithm REINFORCING STEEL imaging instrument Sensor systems

来源：评论

学校读者我要写书评

暂无评论

A novel image enhancement algorithm to determine the dust level on photovoltaic (PV) panels

引用

RENEWABLE ENERGY 2022年第Part1期201卷 172-180页

作者： Fan, Siyuan Wang, Xiao Wang, Zun Sun, Bo Zhang, Zhenhai Cao, Shengxian Zhao, Bo Wang, Yu Northeast Elect Power Univ Sch Automat Engn Jilin 132012 Peoples R China China Power Huachang Suzhou Elect Power Technol Re Suzhou 215123 Peoples R China Elect Power Res Inst Guizhou Power Grid Co Ltd Guiyang 550000 Peoples R China Army Engn Univ PLA Chongqing 400035 Peoples R China Northeast Elect Power Univ 169 Changchun Rd Jilin Peoples R China

An accurate evaluation of the dust accumulation on photovoltaic (PV) panels enables the development of cleaning plans and improves the grid connection security of PV power stations. In this paper, a novel image enhancement algorithm is proposed to evaluate the dust accumulation on PV panels. An atmospheric scattering model was used to analyze the difference in the image characteristics of clean and dusty PV panels. A model was proposed to describe the relationship between the model coefficient and the dust level by minimizing the pixel difference between the images of the soiled and clean PV panels. An experiment system was designed to acquire the images of clean and soiled PV panels with different dust levels. The model parameters were determined by data fitting, and the model's generalization ability was improved by adding a noise item. The results show that the model can estimate the dust level on PV panels with an accuracy of 83.78%. The average root mean square error (RMSE) of samples 1-4 is 1.67, and the error range is 2-3.5 g/m2. In addition, the proposed method has higher accuracy than the optical attenuation and weighing methods, with a mean absolute error (MAE) of 1.61 g/m2. The method is simple and reliable for intelligent cleaning of PV panels.

关键词： image enhancement algorithm Dust level PV panels Light transmission

来源：评论

学校读者我要写书评

暂无评论

Internet Model Construction of Football Sports Propagation based on Automatic Camera Action Collection and image enhancement algorithm 5

Internet Model Construction of Football Sports Propagation b...

引用

5th International Conference on Inventive Computation Technologies (ICICT)

作者： Hu, Hongquan Liaocheng Univ Sch PE Liaoccheng Shandong Peoples R China

ISBN: (数字)9781665408370

ISBN: (纸本)9781665408387;9781665408370

In this paper, a video signal acquisition system is designed based on the input capture function of the HCS12 single-chip microcomputer for automatic wonderful motion acquisition by the camera. In this system, the output signal of the CMOS camera is binarized, and a color restoration and image denoising network is designed to solve the problems of color distortion and noise amplification in the enhanced image. image quality and visual effects, extracting shape features of black guide lines. Analyze the wireless channel quality of football live broadcast in the network model from the overall, local and individual levels, in order to provide theoretical reference for players' passing performance evaluation and targeted preparation.

关键词： Internet Model Construction Football Sports Propagation Automatic Camera Action image enhancement algorithm

来源：评论

学校读者我要写书评

暂无评论

Application of image enhancement algorithm in Multi-Phase Flow CT System

Application of Image Enhancement Algorithm in Multi-Phase Fl...

引用

3rd International Conference on Mechanical and Electronics Engineering (ICMEE 2011)

作者： Ma, Min Ji, Jingjing Zhang, Caixia Civil Aviat Univ China Aviat Automat Inst Tianjin Peoples R China

ISBN: (纸本)9783037852866

In this paper, image enhancement algorithm is applied to multi-phase CT system imaging. Aiming at artifact imaging of multiphase flow CT system image reconstruction, this paper uses image enhancement algorithm to enhance the reconstructed image. The simulation results prove that with a small amount projection angle data about reconstruction it can also get clear images by using image enhancement algorithm processing and also remove artifacts for reconstructed image. It is efficient to shorten the multi-phase CT system image reconstruction data collection time, and benefit to analysis multi-phase transient flow pattern.

关键词： image enhancement algorithm CT system image reconstruction multiphase flow

来源：评论

学校读者我要写书评

暂无评论

Multi-scale Retinex image enhancement algorithm Based on Fabric Defect Database

Multi-scale Retinex Image Enhancement Algorithm Based on Fab...

引用

International Conference on Optical Instruments and Technology - Optoelectronic Imaging/Spectroscopy and Signal Processing Technology

作者： Wang, Huang Duan, Fajie Zhou, Weiti Tianjin Univ State Key Lab Precis Measuring Technol & Instrume Tianjin 300072 Peoples R China Hubei Univ Technol Sch Mech Engn Wuhan 430068 Hubei Peoples R China

ISBN: (纸本)9781510636552

In order to meet the demands of fabric defect detection under different lighting conditions, the multi-scale Retinex algorithm is proposed as preprocessing algorithm to limit the influence of lighting change on subsequent processing to a certain degree. Firstly, the fabric defect simulation database under complex lighting conditions is produced by rotating, flipping and transforming the data based on traditional TILDA fabric texture database. Aiming at the phenomenon of the obvious brightness changes between different images in the database and the more complicated illumination environment, the multi-scale Retinex algorithm as the preprocessing is used by logarithmically transforming the given input image and estimating the incident image in this paper. The input image and the estimated incident image are reflected images, which limits the influence of illumination changes on subsequent processing to a certain extent. The comparative experiments show that dynamic range compression, color constancy, edge enhancement and a balance between the three aspects can be achieved by the multi-scale Retinex algorithm at the same time. The experimental results show that the multi-scale Retinex algorithm is robust, and the local details of the processed image will be well maintained. The image information entropy and contrast is increased by 30%, and average gradient is increased by nearly 40%. Simultaneously, the change of light and noise will be limited to a certain degree, and high-quality fabric image under different illumination conditions can be obtained effectively.

关键词： Complex illumination Fabric defect Simulation data base image enhancement algorithm

来源：评论

学校读者我要写书评

暂无评论

Research and analysis of deep learning image enhancement algorithm based on fractional differential

引用

CHAOS SOLITONS & FRACTALS 2020年 131卷 109507-109507页

作者： Liu, Kai Tian, Yanzhao Lvliang Univ Dept Comp Sci & Technol Lvliang 033000 Peoples R China Beijing Univ Posts & Telecommun Informat Secur Ctr Beijing 100876 Peoples R China

Aiming at the characteristics of the image processing technology course and the practicality, the deep learning and fractional differential wavelet algorithm are introduced into the image processing technology to solve the problem that the traditional algorithm loses the texture detail information during image enhancement. Through theoretical analysis, the fractional differential wavelet algorithm can greatly improve the high frequency components of the signal, enhance the IF component of the signal, and the very low frequency of the nonlinear retained signal. According to this, the application of fractional differential to image enhancement will make the edge of the image prominent. The enhanced image with clearer texture and image smoothing area information is preserved. Then, based on the classical fractional differential definition, the fractional difference equation is derived and the differential operator of the approximate depth learning method is constructed. Experiments with image enhancement show that the image enhancement method based on fractional differential operator is better than the traditional integer differential method. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Fractional differential Deep learning image enhancement algorithm Wavelet transform

来源：评论

学校读者我要写书评

暂无评论

A Review of Robust image enhancement algorithms and Their Applications 4

A Review of Robust Image Enhancement Algorithms and Their Ap...

引用

4th IEEE International Conference on Smart Energy Grid Engineering (SEGE)

作者： Irmak, Emrah Ertas, Ahmet H. Karabuk Univ Elect & Elect Engn Karabuk Turkey Karabuk Univ Biomed Engn Karabuk Turkey

ISBN: (纸本)9781509051113

The essential target of image enhancement is to minimize noise from a digital image by keeping the intrinsic information of the image preserved. The main difficulty in image enhancement is determining the criteria for enhancement and, therefore, more than one image enhancement techniques are empirical and require interactive procedures to obtain satisfactory results. In this paper robust image enhancement algorithms are discussed, implemented to noisy images and compared according to their robustness. The algorithms are especially able to improve the contrast of medical images, fingerprint images and selenography images by means of software techniques. When deciding that one image has better quality than another image, quality measure metrics are needed. Otherwise comparing image quality just by visual appearance may not be objective because images could vary from person to person. That is why quantitative metrics are crucial to compare images for their qualities. In this paper Peak Signal to Noise Ratio (PSNR) and Mean Squared Error (MSE) quality measure metrics are used to compare the image enhancement methods systematically. All the methods are validated by the performance measures with PSNR and MSE. It is believed that this paper will provide comprehensive reference source for the researchers involved in image enhancement field.

关键词： image enhancement algorithm histogram matching histogram equalization fuzzy set theory

来源：评论

学校读者我要写书评

暂无评论

Research and Implementation of Digital image enhancement algorithms

Research and Implementation of Digital Image Enhancement Alg...

引用

International Conference on Electronic Information Technology and Computer Engineering (EITCE)

作者： Liu Yue Li Meishan Ma Dandan Liu Desheng Jiamusi Univ Coll Informat Sci & Elect Technol Jiamusi 154007 Peoples R China

ISBN: (纸本)9781510850491

From the viewpoint of technique orientation, this article has realized several image enhancement techniques, which have been proved to be effective, by means of Delphi8.0 language. The experiment indicated that this procedure may be fast and accurately carried on the gradation transformation to the gradation picture and center the value filter and that can make the picture contrast gradient strengthened, the noise eliminated and the picture quality was improved.

关键词： image enhancement technique image enhancement algorithm grade Digital images Comment Noise algorithms Refractive surgery enhancement Fasting

来源：评论

学校读者我要写书评

暂无评论

Criteria to evaluate the fidelity of image enhancement by MSRCR

引用

IET image PROCESSING 2018年第6期12卷 880-887页

作者： Liu, Yuhong Yan, Hongmei Gao, Shaobing Yang, Kaifu Univ Elect Sci & Technol China MOE Key Lab Neuroinformat Chengdu Brain Sci Inst Clin Hosp Chengdu Sichuan Peoples R China Chengdu Med Coll Dept Phys Chengdu Sichuan Peoples R China Sichuan Univ Coll Comp Sci Chengdu Sichuan Peoples R China

image fidelity refers to the ability of a process to render an image accurately. As image enhancement algorithms have been developed in recent years, how to assess the performances of different image enhancement algorithms has become an important question. Some objective image quality assessment (IQA) methods have been proposed, but there is little research on the image fidelity evaluation when comparing the performances of enhancement algorithms. Therefore, the authors proposed a new image fidelity assessment framework consisting of three components: the information entropy fidelity, constituent fidelity and colour fidelity. To verify the rationality of the fidelity criteria, they used the popular IQA database (LIVE), and the results indicated that the method matched better with the subjective assessment. Then, they verified the effectiveness of their method with the famous technique of image enhancement: multi-scale Retinex with colour restoration (MSRCR). The experimental results demonstrate MSRCR can improve the image quality, but it gives rise to obvious distortions. It is necessary to keep a moderate balance between image fidelity and image quality when they assess the enhanced images. Their results showed that the proposed objective fidelity index could provide an additional objective basis for the quality evaluation of image enhancement algorithms.

关键词： image enhancement rendering (computer graphics) entropy image colour analysis image restoration MSRCR image enhancement algorithm objective image quality assessment method IQA method image fidelity assessment framework information entropy fidelity constituent fidelity colour fidelity LIVE multiscale Retinex with colour restoration

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：