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检索条件"任意字段=2021 International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2021"

共 679 条记录，以下是261-270 订阅

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Color Endoscopic image Enhancement Technology Based on Nonlinear Unsharp Mask and CLAHE 6

Color Endoscopic Image Enhancement Technology Based on Nonli...

引用

6th international conference on signal and image processing, ICSIP 2021

作者： Fang, Shanshan Xu, Chao Feng, Bo Zhu, Yuzhe School of Electronics and Information Engineering AnHui University AnHui Engineering Laboratory of Agro-Ecological Big Data HeFei China

ISBN: (纸本)9780738133737

Since the existing endoscopic image enhancement algorithms cannot take into account the problems of detail enhancement, brightness preservation and color preservation, this paper proposes an endoscopic image enhancement based on an improved unsharp mask and CLAHE algorithm. First, perform local brightness adjustment and saturation correction on the input image, and secondly, it is also the key point to perform contrast enhancement, which is divided into low-frequency background enhancement and high-frequency detail enhancement. CLAHE is used to balance the background intensity of low frequency components, and then the high-frequency parts are nonlinearly sharpened. The improved nonlinear transfer function proposed is used, and the high-frequency texture part is emphasized in combination with canny edge detection. Finally, the objective and subjective quality assessment of the image is carried out. The results show that the proposed nonlinear method enriches the texture details such as blood vessels. The peak signal-to-noise ratio and Tenengrad gradient are better than those of the compared algorithm. and the algorithms in this paper are all enhanced in the brightness channel, which has the function of color preservation, so as to achieve the natural enhancement effect as much as possible. © 2021 IEEE.

关键词： image enhancement

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AFDN: ATTENTION-BASED FEEDBACK DEHAZING NETWORK FOR UAV REMOTE SENSING image HAZE REMOVAL

AFDN: ATTENTION-BASED FEEDBACK DEHAZING NETWORK FOR UAV REMO...

引用

IEEE international conference on image processing (ICIP)

作者： Wang, Shan Wu, Hanlin Zhang, Libao Beijing Normal Univ Sch Artificial Intelligence Beijing 100875 Peoples R China

ISBN: (纸本)9781665441155

To efficiently remove haze in unmanned aerial vehicle (UAV) remote sensing images, a novel attention-based feedback dehazing network (AFDN) is proposed, which is constructed by feedback connections and attention-based feedback blocks (AFBs). It has three major advantages compared with other dehazing algorithms: 1) The feedback connections, which allow network to use previous state to improve current performance, can effectively help the proposed AFDN generate clear remote sensing scenes progressively. 2) The AFBs are specially designed to extract global residual features, in which the dual attention block can usefully reduce redundant information and improve the fitting ability of network. 3) To obtain abundant texture information from UAV remote sensing images and restore real ground surfaces, an energy loss is employed for texture features learning. Experiments on synthetic datasets and real UAV remote sensing images verify the superiority of AFDN over several state-of-the-art methods in terms of qualitative and quantitative analysis.

关键词： image enhancement remote sensing image dehazing feedback mechanism CNN

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Automated total micro-IBA using advanced image processing and Machine Learning 25

Automated total micro-IBA using Advanced Image Processing an...

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25th international conference on Ion Beam Analysis and 17th international conference on Particle Induce X-Ray Emission, IBA-PIXE 2021 and 23rd international conference on Secondary Ion Mass Spectrometry, SIMS 2021

作者： Solis-Lerma, D. Khodja, H. Université Paris-Saclay CEA CNRS NIMBE LEEL Gif-sur-Yvette91191 France

We have developed a Python code that aims at automatizing the analysis of generic micro-IBA data by associating statistical methods and machine learning algorithms. The code is organized in two parts: hyperspectral image analysis and composition prediction. In the first stage, main phases and local anomalies are detected separately using PCA and DWEST methods, respectively. In the prediction stage, we use the model generated by a trained artificial neural network. The network is fed with simulated particle and x-ray spectra generated from the SIMNRA and Gulys software codes. For particle spectra, we paid particular attention to the cross section selection that goes beyond already implemented SIMNRA functionalities. To limit the impact of the simulation time on the overall code performance, we make use of data augmentation. When using simulated data as input, we found that the trained neural network predicts stoichiometries and thicknesses with an excellent agreement, even for complex targets composed of several elements and layers. Regarding realistic experimental data, we still get reasonable predictions but remain dependant of cross section quality. The code can combine data from RBS, NRA, ERDA and PIXE and should pave the way for fully automatized micro-ion beam analysis. © Published under licence by IOP Publishing Ltd.

关键词： Forecasting

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Comparison of Encryption Techniques to Encrypt Private Parts of an image

Comparison of Encryption Techniques to Encrypt Private Parts...

引用

international conference on Advances in Electrical and Computer Technologies, ICAECT 2021

作者： Shetty, Nisha P. Muniyal, Balachandra Kaithi, Rithish Reddy Yemma, Sarath Chandra Reddy Manipal Institute of Technology Manipal Academy of Higher Education Manipal576104 India

ISBN: (纸本)9789811911101

This article compares two methods for encrypting private information of the image and to make the image data highly secure. One method implements the advanced least significant bit (LSB) steganography, AES encryption, and RSA algorithm by matching data to an image, and there is much less chance of an attacker having the capacity to apply steganography analysis to recover original data. Before concealing the key in an image encrypted using AES algorithm with same key, the application first encrypts it using RSA and LSB methods (Moumen and Sissaoui in Nonlinear Engineering 6:53–59, 2017 [1]). The other method implements an image encryption algorithm derived from SHA-512 (Seyedzade, et al. in Iranian conference on machine vision and image processing, No. 5941167, 2010 [2]). In this algorithm, first equal half of data in image is used to encrypt opposite half of the image reciprocally. In order to assess performance, both the algorithms are examined to analyze the measure of the security, quality, and efficiency. These assessments consist of histogram analysis, coefficient of correlation analysis, information entropy analysis, degree of quality in encryption. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Steganography

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Active-Passive Radar for Radar Imaging from Aerospace Carriers 19

Active-Passive Radar for Radar Imaging from Aerospace Carrie...

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19th international conference on Smart Technologies (IEEE EUROCON)

作者： Pavlikov, Volodymyr Volosyuk, Valeriy Zhyla, Simeon Tserne, Eduard Shmatko, Olexandr Sobkolov, Anton NAU Kharkiv Aviat Inst Aerosp Radioelect Syst Dept Kharkiv Ukraine

ISBN: (纸本)9781665432993

algorithms for radar imaging of the underlying surface from aerospace carriers have been synthesized. In doing so, we have considered two possible ways of image reception based on methods of active and passive remote sensing. On this basis, a radar complex, which allows forming images proportional to either the specific effective surface scattering or the effective noise temperature of the underlying surface, has been created. The structural scheme of the complex in accordance with both operating modes is developed. The results of radio image simulation are given.

关键词： radar imaging signal processing algorithm image filtration ultrawideband signals

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Improved BM3D for Real image Denoising 13

Improved BM3D for Real Image Denoising

引用

13th international conference on Wireless Communications and signal processing, WCSP 2021

作者： Lin, Tianhui Hong, Hui Wu, Linhuang Fuzhou University College of Physics and Information Engineering Fuzhou China

ISBN: (纸本)9781665407854

Block-matching and 3D filtering (BM3D) and most of its improved algorithms assume that the intensity of the noise image is known, while the real image does not know the specific noise intensity. Moreover, many noise estimation methods have the problem that the estimated value is smaller than the true value. In this case, there will be a problem that the denoising effect of BM3D is not up to expectations. Therefore, we propose an improved BM3D algorithm. A local noise variance estimation algorithm combined with block matching is added to the traditional BM3D to obtain the noise variance of the target block and let it participate in subsequent calculations. The experimental results show that the improved algorithm solves the shortcoming that BM3D cannot directly denoise the real image. At the same time, the algorithm solves the problem that the overall noise variance estimate of the image is too small, which leads to the poor denoising effect of BM3D. © 2021 IEEE.

关键词： image denoising

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Perceptual Evaluation of Low-light image Enhancement algorithms 2021

Perceptual Evaluation of Low-light Image Enhancement Algorit...

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3rd international conference on image, Video and signal processing, IVSP 2021

作者： Wang, Yuxuan Yan, Jia Electronic Information School Wuhan University Wuhan China

ISBN: (纸本)9781450388917

images taken in low-light environment often face with low dynamic range or color shift caused by lack of illumination. Although many algorithms have been proposed to enhance these images, not much effort has been made on quality assessment of these enhancement results. In our work, we built a database which contains 30 low-light images (both outdoor and indoor scene included) and enhanced images processed by 11 enhancement algorithms. We conducted a subjective experiment based on this database. We found that no algorithm can behave best with images in all situations. Generally, learning-based methods behave better. Further, we also did objective assessment on the database. © 2021 ACM.

关键词： image enhancement

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Leveraging deep learning algorithms for classification of tomato leaf diseases 6

Leveraging deep learning algorithms for classification of to...

引用

6th IEEE international conference on signal processing, Computing and Control, ISPCC 2021

作者： Singh, Karanjeet Rai, Prashant Singla, Kanika Sharda University School Of Engineering And Technology Gr. Noida India

ISBN: (纸本)9781665425520

Tomato leaf disease has a significant impact on tomato yield. Identifying agricultural diseases is critical for the agricultural sector. Detecting and classifying different tomato diseases is often labor intensive and cumbersome. It is difficult to discover subtle distinguishing traits in different tomatoes disease images, which makes the task of visual categorization of the tomato leaf, based images both challenging and ambiguous. This causes huge scope destruction of harvests, diminishes development and ultimately prompts monetary loss of farmers. Septoria leaf spot, late blight, the bacterial spot, and yellow curved leaf diseases affect the crop quality of tomatoes are a few examples. The implementation's most important difficulty was deciding on a deep learning ***, to address this problem, our workexploits few of the widely used deep learning-based modelslike ResNet50 and InceptionV3Through qualitative analysis, the significance of the deep learning models has been highlighted. © 2021 IEEE.

关键词： image classification

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Proceedings - 2021 5th international conference on Imaging, signal processing and Communications, ICISPC 2021

Proceedings - 2021 5th International Conference on Imaging, ...

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5th international conference on Imaging, signal processing and Communications, ICISPC 2021

ISBN: (纸本)9781665424257

The proceedings contain 17 papers. The topics discussed include: detecting falling rocks by estimating excavation points using laser pointer;a real-time target tracking algorithm based on improved kernel correlation filter;constant false alarm OMP algorithm based on sparse ISAR imaging of stationary aircraft target;detection of anal sac disease, Atresia Ani and rectal prolapse for Canis lupus familiaris using image processing and convolutional neural network;investigation of gas/oil/water distribution based on electrical capacitance and microwave tomography;lung nodule classification of CT images based on the deep learning algorithms;the research on the impact of visual image perception in a user interface on typeface design;and joint robust transmit and receive beamforming based on probability constraint.

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Hyper-Parameters Tuning for Hyperspectral image Classification 6

Hyper-Parameters Tuning for Hyperspectral Image Classificati...

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6th IEEE international conference on signal processing, Computing and Control, ISPCC 2021

作者： Chava, Sai Swagath Gunnapaneni, Satya Lakshmi Tejaswini Chakravarty, Sujata Centurion University Of Technology Management Department Of Computer Science And Engineering Andhra Pradesh India

ISBN: (纸本)9781665425520

Hyperspectral imaging is being applied in the field of Cosmology, farming, bioinformatics, medical devices, geology, physics, monitoring are some of the fields covered. However, the hyperspectral data are multi-dimensional and noisy. Hence, it is challenging to classify data for meaningful use. Different machine learning algorithms are being used for classification. In this paper, three datasets namely such as Botswana, Pavia University Scene, Kennedy Space Center having spectral band of 145, 103 and 176 respectively have been taken. Random forest and Support vector machines (SVM) algorithm have been used. The grid search method is used for tuning and finding out the best parameters for the respective model. The results obtained before and after tuning the hyperparameters have been compared. It has been discovered that the latter delivers superior results. © 2021 IEEE.

关键词： Support vector machines

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