检索结果-内蒙古大学图书馆

The FRIT-based image enhancement algorithm for faint pavement cracks

LASERS IN ENGINEERING 2007年第5-6期17卷 295-310页

作者： Gang, Wang Liang, Xiao He An-Zhi Nanjing Univ Sci & Technol Sch Sci Nanjing 210094 Prov JiangSu Peoples R China LUDong Univ Sch Phys & Elect Engn Yantai 264025 Prov ShanDong Peoples R China

Due to various circumstances, such as non-uniform lighting, weather conditions, and different pavement materials on surfaces, the pavement cracks are hardly distinguishable by eye in a complicated background. In this paper, a novel algorithm for the enhancement of faint cracks was proposed based on the finite ridgelet transform (FRIT). Furthermore we proposed the improvements on the initial design of the FRIT in order to have better energy compaction and to reduce the "wrap-around" effect. The FRIT approach, with its "built-in" linear geometrical structure, provided a more elegant way of enhancing the linear singularities and suppressing the noise. In general, the pavement cracks show the curved feature as a whole. A smooth partition method was proposed to divide the pavement crack image into localised windows where the crack looks straight. Then, we could apply the FRIT-based enhancement method in each window. Experimental results show that the new algorithm outperforms wavelets in enhancing the low-quality images with linear singularities.

关键词： FRIT Randon transform enhancement algorithm smooth partition faint pavement cracks

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Multi-scale decomposition enhancement algorithm for surface defect images of Si3N4 ceramic bearing balls based on stationary wavelet transform

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ADVANCES IN APPLIED CERAMICS 2021年第1期120卷 47-57页

作者： Yu, Dongling Zhu, Zuoxiang Min, Jianliang Fang, Changfu Liao, Dahai Wu, Nanxing Jingdezhen Ceram Inst Sch Mech & Elect Engn Jingdezhen 333403 Peoples R China Sun Yat Sen Univ Sch Technol Guangzhou Peoples R China Natl Engn Res Ctr Domest & Bldg Ceram Jingdezhen 333001 Peoples R China

In order to improve the detection efficiency and image quality of Si3N4 ceramic bearing balls surface defects, digital image processing technology is used to analyse the information characteristics of Si3N4 ceramic bearing balls surface. A multi-scale decomposition enhancement algorithm for surface defect images of Si3N4 ceramic bearing balls based on the stationary wavelet transform is proposed. By building the surface defects detection system of Si3N4 ceramic bearing balls, the image enhancement program based on stationary wavelet transform with index low-pass filtering and nonlinear transform enhancement is designed. Finally, the effectiveness of the algorithm is verified by experiments. The experimental results show that the algorithm is applied to the surface defects image of Si3N4 ceramic bearing balls can effectively weaken the background noise and surface grinding texture, and enhance the contrast between defects and background clearly. In addition, the binary image is obtained by an adaptive threshold binary algorithm. After removing the tiny points by morphological opening operation, the defects are accurately and completely segmented, and then the Canny operator is used for edge detection to extract the edge contour of defects. When the decomposition level is set to 3, the average calculation time is 0.88 s, which are relatively short and have sufficient precision, and the algorithm can be extended to other kinds of ceramic ball surface damage detection.

关键词： Stationary wavelet transform multi-scale decomposition Si3N4 ceramic bearing balls surface defects enhancement algorithm

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An Improved enhancement algorithm Based on CNN Applicable for Weak Contrast Images

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IEEE ACCESS 2020年 8卷 8459-8476页

作者： Wang, Jiao Hu, Yanzhu Beijing Univ Posts & Telecommun Sch Automat Beijing 100876 Peoples R China

Image enhancement is commonly used in digital image processing applications. Through image enhancement, the features of the target object are enhanced to make it easier to identify. In order to realize image enhancement, a neural network with a trapezoidal convolution kernel is proposed in this paper. First, weak contrast images are generated using the images in SIDD, DND and RENOIR, which are public datasets used for image denoising. On this basis, pixel distribution characteristics of the R, G and B channels of the weak contrast images are analyzed, and the histogram distribution of the images is given, which can be used to determine the size of the network convolution kernels. Then, a multi-layer convolution neural network is constructed, which uses the original image as an input and outputs the noise map. This network includes convolution kernels of different sizes for the three channels of the original images, and the convolution kernel size is determined by calculating the mean square deviation of the pixels of the corresponding channel. The proposed algorithm provides visually pleasing contrast enhancement. In this paper, a public dataset for image enhancement and actual captured images are separately assessed, both the contrast experiment and ablation experiment results show that the algorithm proposed in this paper can achieve a higher Peak Signal to Noise Ratio (PSNR) and a higher Structural Similarity Index (SSIM) than other image enhancement algorithms.

关键词： enhancement algorithm trapezoidal convolution Kernel image contrast feature analysis neural network

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Reliability enhancement algorithm of Human Motion Recognition Based on Knowledge Graph

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INTERNATIONAL JOURNAL OF DISTRIBUTED SYSTEMS AND TECHNOLOGIES 2021年第1期12卷 1-15页

作者： Wang, Yongwei Feng, Feng Capital Normal Univ Beijing Peoples R China

In order to solve the problem of uneven spatial distribution of human motion image and low peak signal-to-noise ratio (PSNR) of image reliability enhancement, a reliability enhancement algorithm for human motion recognition based on knowledge graph is proposed. An automatic spatial planning model of human motion image is constructed. The human motion spatial features are sampled, and the three-dimensional contour feature reconstruction model is established. The human motion spatial contour structure is reconstructed by adaptive edge feature detection method, and the knowledge graph of the motion image is extracted. Multi-scale information enhancement method is used to enhance and recognize the reliability of human motion image. The experimental results show that the method has the advantages of good reliability, high signal-to-noise ratio of image enhancement, and high accuracy of human motion recognition.

关键词： enhancement algorithm Human Motion Recognition Knowledge Graph Reliability

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Weak illumination image enhancement algorithm based on cyclic generation countermeasure network

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JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2022年第6期22卷 2121-2133页

作者： Zhang, Yu Henan Finance Univ Coll Software Technol Zhengzhou 450046 Henan Peoples R China

To solve the problem of missing or distorted detail texture when manually adjusting image parameters, a weak illumination image enhancement algorithm based on cyclic generation game network is proposed. The image features are normalized by Gaussian distribution. Combined with homomorphic filtering theory and defogging operation, the image is generated and denoised according to the network brightness to enhance the weak illumination image. The experimental results show that after using this method to process the image, the image entropy increases by 6.8%, the contrast increases by 27.5%, and the noise content decreases by 24.1%. It has better contrast. It can not only meet the enhancement effect of weak light, but also ensure the details of the image, so that the image has richer details and good visual appearance.

关键词： Cyclic generation countermeasure network weak illumination image enhancement algorithm normalization treatment brightness sensitivity

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Low Illumination Image enhancement algorithm Based on Convolutional Neural Network 1

Low Illumination Image Enhancement Algorithm Based on Convol...

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1st IEEE International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics, AIKIIE 2023

作者： Song, Wei Zhang, Wei College of Information Science and Technology Bohai University Jinzhou China

ISBN: (纸本)9798350316469

Image enhancement processing is to improve image quality and obtain more image information. Due to the limitation of image acquisition equipment and the influence of external environment, the acquired images have some problems such as low contrast, color distortion and loss of detail information, which seriously affect the subsequent application of images. Therefore, how to achieve low illumination image enhancement and obtain high quality image has become an important research field. Based on convolutional neural network technology, this paper studies the image quality evaluation indexes such as peak signal-to-noise ratio and structural similarity, designs ResNet network structure and U-Net network structure, and studies the image enhancement effects of two types of convolutional neural networks. The research results have a good enhancement effect, and the enhanced image is closer to the real natural image, so as to improve people's experience of using the image. It is found that U-Net network is superior to ResNet network in the enhancement of low illumination image. The improved illuminance map enhancement network can enhance the illumination component of different brightness regions in the image. © 2023 IEEE.

关键词： convolutional neural network enhancement algorithm low illumination image ResNet network U-Net network

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Computer-aided visual communication design based on image detail enhancement algorithm

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Optical and Quantum Electronics 2024年第4期56卷 652-652页

作者： Jiang, Jian School of Computer and Electrical Engineering Hunan University of Arts and Science Hunan ChangDe 415000 China

There is a problem of unclear image details in traditional visual communication design, which can affect the effectiveness of the design work. This article proposes a computer-aided design method based on image detail enhancement algorithms. The core idea of this method is to improve the detail representation of images by using image detail enhancement algorithms, thereby making the design work clearer and more vivid. Firstly, preprocess the image to improve its quality and clarity. Then, an enhancement algorithm is used to enhance the details of the image, highlighting the details in the image to make it more distinct. Finally, post processing is performed on the enhanced image to make the image details more prominent and meet the design requirements. By analyzing the experimental results of computer-aided visual communication design using image detail enhancement algorithms, this article found that this algorithm can significantly improve the detail representation of design works and enhance the visual communication effect. Compared with traditional design methods, design works using image detail enhancement algorithms are clearer and more vivid, which can better attract the attention of the audience and convey design intentions. This verifies the effectiveness and practicality of the proposed algorithm. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Computers enhancement algorithm Image details Visual communication

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Quality Assessment for Comparing Image enhancement algorithms 27

Quality Assessment for Comparing Image Enhancement Algorithm...

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27th IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Chen, Zhengying Jiang, Tingting Tian, Yonghong Peking Univ Sch Elect Engn & Comp Sci Beijing Peoples R China

ISBN: (纸本)9781479951178

As the image enhancement algorithms developed in recent years, how to compare the performances of different image enhancement algorithms becomes a novel task. In this paper, we propose a framework to do quality assessment for comparing image enhancement algorithms. Not like traditional image quality assessment approaches, we focus on the relative quality ranking between enhanced images rather than giving an absolute quality score for a single enhanced image. We construct a dataset which contains source images in bad visibility and their enhanced images processed by different enhancement algorithms, and then do subjective assessment in a pair-wise way to get the relative ranking of these enhanced images. A rank function is trained to fit the subjective assessment results, and can be used to predict ranks of new enhanced images which indicate the relative quality of enhancement algorithms. The experimental results show that our proposed approach statistically outperforms state-of-the-art general-purpose NR-IQA algorithms.

关键词： enhancement algorithm quality assessment

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An Image Segmentation Method Using Image enhancement and PCNN with Adaptive Parameters

An Image Segmentation Method Using Image Enhancement and PCN...

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2nd International Conference on Mechatronics and Intelligent Materials (MIM 2012)

作者： Cai, Hong Zhang, Xueyuan Dai, Haitao Zhou, Dongming Yunnan Univ Informat Coll Kunming 650091 Peoples R China

ISBN: (纸本)9783037853849

PCNN model is particularly suitable for image segmentation and edge extraction, but its effect depends on the selection of parameters in PCNN model and network iteration settings, which needs for a large number of artificial interaction and has limited PCNN image processing practicality. In this paper, through combining statistical properties of images and PCNN model, we present an adaptive algorithm based on the distribution of pixels to replace the artificial interaction. Experimental results show that image segmentation using image enhancement and PCNN with adaptive parameters is significantly better than the traditional PCNN image segmentation and verify the effectiveness of the method.

关键词： PCNN enhancement algorithm Adaptive parameters Image segmentation

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Image enhancement Using Bright Channel Prior

Image Enhancement Using Bright Channel Prior

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2nd International Conference on Industrial Informatics - Computing Technology, Intelligent Technology, Industrial Information Integration (ICIICII)

作者： Sun, Song Guo, Xinhua Wuhan Univ Technol Sch Automat Wuhan Peoples R China Wuhan Univ Technol Sch Mech & Elect Engn Wuhan Peoples R China

ISBN: (纸本)9781509035755

In view of the low illumination color images, image enhancement technology is commonly used in image processing. In this study, we propose a brightness enhancement algorithm based on the bright channel prior, which focuses on the gray removal. The local patches in sufficient illumination images contain some pixels that have very high intensities in at least one color channel. Using this prior with haze imaging model, image enhancement can be achieved. The experimental results showed that the algorithm had good visual effect in image enhancement.

关键词： image enhancement bright channel brightness enhancement algorithm

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