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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems III"

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ADHHI airborne hyperspectral imager: camera structure and geometric correction 28

ADHHI airborne hyperspectral imager: camera structure and ge...

引用

conference on image and Signal processing for Remote Sensing XXViii

作者： Dong, Jieke Duan, Yansong Zhou, Qi Zhao, Xinbo Wuhan Univ Sch Remote Sensing & Informat Engn Wuhan 430079 Peoples R China

ISBN: (纸本)9781510655386;9781510655379

For decades, the design of remote sensors has to make trade-offs among many characteristics such as the field of view (FOV), spatial resolution, spectral resolution, radiometric resolution, and the number of bands. It's inevitable to weaken some characteristics to enhance others. Moreover, these problems lead to using multi-sources of remote sensing data in practical projects where a single sensor can't meet the relevant requirements. The Airborne Dual-mode High-resolution Hyperspectral imager (ADHHI) provides a new solution to the above limitations by the technology of multi-camera stitching. In this way, many excellent but conflicting characteristics can be separated into different imaging sub-systems, and are combined together during data processing. Supported by related processing algorithms and software, ADHHI embeds many excellent characteristics into one system, such as high spatial resolution, high spectral resolution, and high radiometric resolution. Firstly, this paper picks some common imaging sensors to illustrate the problem of conflicting characteristics. Secondly, we introduce the camera structure and sensor parameters of ADHHI. Then, we sketch out the data processing workflow and elaborate on relevant principles and results of the whole geometric correction, such as homospectral stitching and hetero-spectral registration. Finally, this airborne hyperspectral imager's advantages and application prospects are concluded.

关键词： geometric correction image stitching hyperspectral imager airborne pushbroom

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A Novel Artistic image Compression Algorithm Based on Multi-Scale Adaptive Discrete Wavelet Transform

A Novel Artistic Image Compression Algorithm Based on Multi-...

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Multi-Agent systems for Collaborative Intelligence (ICMSCI), International conference on

作者： Yijun Li China Academy of Art Yuhang District Hangzhou Zhejiang China

ISBN: (数字)9798331509828

ISBN: (纸本)9798331509835

How to compress information is a challenge in the digital age, and the image compression has a wide range of application scenarios. In order to solve the challenges of low compression efficiency and high loss rate of the traditional algorithms, this study proposes a compression algorithm based on multi-scale adaptive discrete wavelet transform. The core of the proposed algorithm is to make reasonable use of the multiresolution analysis characteristics of discrete wavelet transform. Based on the feature extraction, the image information is decomposed into high-frequency and low-frequency parts. This operation can stably and effectively implement frequency domain threshold processing and reduce redundant data. The proposed algorithm optimizes the encoding efficiency of image features to the greatest extent by introducing block difference features and designing a new iterative function system. In view of the high redundancy and high complexity of the artistic images, the traditional wavelet analysis is improved and optimized, and a multi-scale adaptive model is introduced. In the experiment, the test used multiple sets of artistic image test sets and compared them with mainstream algorithms (JPEG, VAE, etc.). In PSNR analysis, the proposed algorithm achieves better performance.

关键词： image coding Wavelet transforms Transforms Discrete wavelet transforms Feature extraction Wavelet analysis Wavelet domain Compression algorithms Frequency-domain analysis Collaborative intelligence

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Segmentation of Electrical Discharge Processes Based on the image Analysis of Plasma-Electrolyte Oxidation 19

Segmentation of Electrical Discharge Processes Based on the ...

引用

conference on Electro-Optical and Infrared systems - Technology and Applications XIX

作者： Zhukov, S. Voronin, V. Semenishchev, E. Chudinov, D. Zhukova, O. Moscow State Univ Technol STANKIN Ctr Cognit Technol & Machine Vis Moscow Russia

ISBN: (纸本)9781510655461

In the process of plasma-electrolytic synthesis, a new physical surface is synthesized, consisting of a metal oxide layer of a modified surface and the synthesis of elements of a set of electrolyte plasma, the nodal sources of the components of which are the components of the electrodes (electrolyte and metal surface). In this regard, the classification of plasma electro-discharge processes based on analyzing optical and electrical sensor data using machine learning methods is an actual task. It can be used for intelligent control algorithms of the sensor layers operations and conduct analytical and quantitative studies of the properties of nodal substances. The paper presents the experimental analysis of video and electrical parameters of the oxygen process, automated processing of the basic features of images of plasma-electrolyte discharges, and a segmentation approach of the electric-discharge machining. This approach can help create microsensor elements and materials and systems for intelligent modeling and launching of electrochemical methods for creating an electrolyte plasma and directed synthesis of substances. To test the performance of the proposed algorithm, the database STANKIN is used.

关键词： segmentation image processing electrical discharge plasma-electrolyte oxidation

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Gaussian Blur through Parallel Computing

Gaussian Blur through Parallel Computing

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International conference on image processing and Vision Engineering (IMPROVE)

作者： Ibrahim, Nahla M. Abou ElFarag, Ahmed Kadry, Rania Arab Acad Sci & Technol & Maritime Transport Dept Comp Engn Alexandria Egypt

ISBN: (纸本)9789897585111

Two dimensional 2D convolution is one of the most complex calculations and memory intensive algorithms used in image processing. In our paper, we present the 2D convolution algorithm used in the Gaussian blur which is a filter widely used for noise reduction and has high computational requirements. Since, single threaded solutions cannot keep up with the performance and speed needed for image processing techniques. Therefore, parallelizing the image convolution on parallel systems enhances the performance and reduces the processing time. This paper aims to give an overview on the performance enhancement of the parallel systems on image convolution using Gaussian blur algorithm. We compare the speed up of the algorithm on two parallel systems: multi-core central processing unit CPU and graphics processing unit GPU using Google Colaboratory or "colab".

关键词： CUDA Parallel Computing image Convolution Gaussian Blur Google Colaboratory

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Wirelessly Controlled Plant Health Monitoring and Medicate System Based on IoT Technology 1st

Wirelessly Controlled Plant Health Monitoring and Medicate S...

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1st International conference on Advanced Network Technologies and Intelligent Computing (ANTIC)

作者： Ayalew, Lijaddis Getnet Mattihalli, Channamallikarjuna Asmare, Fanuel Melak Bahir Dar Univ Fac Elect & Comp Engn Bahir Dar Inst Technol Bahir Dar Ethiopia

ISBN: (纸本)9783030960407;9783030960391

The availability of good quality fruits and vegetables is paramount in preventing starvation and minimizing outbreaks of diseases which leads to improving quality of life. One of the major obstacles of the mentioned availability is plant leaf disease. Although manpower plays a vital role in detecting such problems it is time-intensive, expensive, and very inefficient. Thus, developing a mechanism to vigorously monitor leaf's health and detect diseases of plant leaves at early stages is mandatory so that one can produce plenty. In this contribution, a system that detects leaf disease is developed using image processing algorithms, the k-nearest neighbor (KNN), support vector machine (SVM), and multilayer perception (MLP) machine learning algorithms are compared based on plant disease detection and classification systems performances. We also developed a prototype of simple-to-install technology that can recognize leaf diseases and allow medicine flow based on the results. This paper presents a smart plant health monitoring system that takes into account humidity, temperature, and soil contents.

关键词： image processing IoT KNN MLP SVM

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3D image Reconstruction and processing for Augmented and Virtual Reality Applications: A Computer Generated Environment 2

3D Image Reconstruction and Processing for Augmented and Vir...

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2nd IEEE International conference on Communication, Security and Artificial Intelligence, ICCSAI 2023

作者： Baskar, Radhika Krishnammal, P. Muthu Aeron, Anurag Ali, Syed Sumera Leonid, T. Thomas Arun, M.R. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India School of Electronics Engineering VIT-AP University Andhra Pradesh Amaravati India School of Computing Dit University Computer Science and Engineering Dehradun India Csmss Chh Shahu College of Engineering Electronics and Computer Engineering Department Maharashtra Aurangabad India Ece Dept Kcg College of Technology Chennai India Vel Tech Rangarajan Dr. Sagunthala R&D Science and Technology Department of Ece Chennai India

ISBN: (纸本)9798350369960

New technologies like AR and VR are changing our online and offline experiences. Augmented and virtual reality applications need 3D picture reconstruction and processing. In augmented and virtual reality, this abstract explains 3D image reconstruction and processing concepts, techniques, and effects. Creating engaging AR and VR experiences starts with 3D data. Depth sensors, stereoscopic images, and photogrammetry are essential for accurate 3D reconstructions of real-world objects and settings. These data streams support spatial cognition and interaction in AR/VR. Reconstruction technologies like point cloud and mesh reconstruction are essential for turning 3D data into models. Virtual features that complement or replace the actual environment in AR experiences or build fully fabricated VR settings are based on these models. By applying 2D textures to 3D geometry, 'texture mapping' enhances scene realism. Realtime augmented and virtual reality processing requires effective rendering, tracking, and physics simulation algorithms. Rendering engines provide beautiful, responsive experiences, while SLAM lets users explore and interact with virtual information in real life. Occlusion culling and level-of-detail rendering are two optimisation methods needed for smooth performance on high-end VR systems and mobile AR devices. Virtual reality is defined by 3D object interaction and control. Natural and engaging interfaces are created using gesture detection and real-time physics simulations. AR and VR software developers encounter new challenges with each iteration. AR requires accurate spatial mapping, dependable tracking, and simple user interfaces to blend the virtual and real worlds. In contrast, virtual reality (VR) immerses users in realistic computer settings. Portability across operating systems is crucial for greater adoption. Developers must optimise programmes for several hardware platforms to reach the most people. © 2023 IEEE.

关键词： 3D image Augmented reality Reconstruction Virtual Reality

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Real-Time PageRank on Dynamic Graphs 23

Real-Time PageRank on Dynamic Graphs

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32nd International Symposium on High-Performance Parallel and Distributed Computing (HPDC) part of the ACM Federated Computing Research conference (FCRC)

作者： Sallinen, Scott Luo, Juntong Ripeanu, Matei Univ British Columbia Vancouver BC Canada

ISBN: (纸本)9798400701559

Modern data generation has grown to enormous proportions, with events occurring at increasingly higher rates. Yet for graph analytics, this growth in scale and velocity has not been matched by improved algorithm or infrastructure techniques: most systems still focus on post-mortem or static analysis. This paper builds on an efficient graph processing abstraction that enables online analysis of dynamically evolving graphs at scale. Integral to this abstraction is that events tied to both graph topology changes as well as algorithmic maintenance occur and are processed asynchronously, concurrently, and autonomously (i.e., without shared state). We offer a case study for online analytics of an evolving graph and make two key contributions: on the one side, we develop an online solution for PageRank. This solution tracks vertices' Page-Rank scores as a graph evolves over time, and quickly converges identically to the result offered by the well-known power iteration method when requested by the user. On the other side, we show that fine-grained temporal analysis of evolving PageRank scores in real-time is feasible. Our approach offers generic applicability, as it: (i) works for directed or undirected graphs, on generic or personalized PageRank, (ii) handles sink vertices correctly, (iii) handles topology changes and complex temporal sliding-window graphs, and (iv) scales to billion edge graphs even on commodity hardware.

关键词： graph processing asynchronous algorithms dynamic graphs

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Recent advancements in image Steganography using Generative Adversarial Networks methods

Recent advancements in Image Steganography using Generative ...

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Intelligent algorithms for Computational Intelligence systems (IACIS), International conference on

作者： Syeda Imrana Fatima Yugandhar Garapati Department of Computer Science & Engineering GITAM (Deemed to be University) Hyderabad India

ISBN: (数字)9798350360660

ISBN: (纸本)9798350360677

Generative Adversarial Networks are employed by GAN-based models in image steganography to efficiently conceal information from images while preserving their visual integrity. These models are made up of two primary parts: the discriminator which determines if an image is a real image or a stego-image, and the generator which embeds the hidden data into images. The generator learns how to embed data in a way that minimizes obvious distortions through adversarial training, where the discriminator and generator fight to make the hidden data less noticeable to detection algorithms and human observers. High data capacity and versatility are strengths of GAN-based steganography models, which enable efficient data concealment across a variety of image formats and steganographic techniques. They dynamically adjust the embedding procedure to strike a compromise between image quality and data capacity. They do, however, come with certain drawbacks such as the need for sophisticated model training, high processing overhead and hyperparameter sensitivity. Notwithstanding these drawbacks, GAN-based techniques mark a substantial breakthrough in the development of delicate and reliable image steganography techniques.

关键词： Training image quality Steganography Visualization Sensitivity Observers Generative adversarial networks Generators Data models Reliability

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processing and Classification algorithms of Medical images

Processing and Classification Algorithms of Medical Images

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International image processing, Applications and systems conference (IPAS)

作者： Oltiana Seitaj Department of Industrial Engineering Electronics Mechanics University of Roma Tre Rome Italy

ISBN: (数字)9798331506520

ISBN: (纸本)9798331506537

This paper evaluates the impact of hybrid deep learning approaches on lung tumor segmentation by combining traditional image processing techniques with advanced AI-driven models. The study integrates Convolutional Neural Networks (CNNs) with preprocessing methods such as noise reduction, adaptive thresholding, and contrast enhancement to address challenges associated with complex anatomical structures and variability in medical image quality. A novel hybrid framework is proposed, leveraging traditional methods to preprocess data and improve input quality for deep learning models, ultimately enhancing segmentation accuracy and *** effectiveness of the proposed approach is assessed using quantitative performance metrics, including Dice Similarity Coefficient (DSC), Hausdorff Distance, Jaccard Index, Precision, and Recall. Preliminary results indicate significant improvements in tumor boundary detection and reduced false-positive rates compared to existing methods. By streamlining segmentation workflows and enabling near-realtime applications in clinical settings, this research offers a pathway to improved diagnostic accuracy, treatment planning, and workflow *** implications include the potential for integration into clinical imaging pipelines, fostering advancements in computer-assisted diagnosis and personalized treatment strategies. This study underscores the value of hybrid methodologies in addressing current limitations and paving the way for more precise and efficient medical image segmentation.

关键词： Deep learning image segmentation Adaptation models Accuracy Thresholding (Imaging) Streaming media Reliability MATLAB Biomedical imaging Tumors

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RGB image Guided Depth Hole-Filling Using Bidirectional Attention Mechanism 1

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17th International conference on Intelligent Information Hiding and Multimedia Signal processing (IIH-MSP) / 14th International conference on Frontiers of Information Technology, Applications and Tools (FITAT)

作者： Chen, Anran Zhao, Yao Lin, Chunyu Beijing Jiaotong Univ Inst Informat Sci Beijing Key Lab Adv Informat Sci & Network Beijing 100044 Peoples R China

ISBN: (数字)9789811910531

ISBN: (纸本)9789811910531;9789811910524

Depth maps obtained by commercial depth sensors are more likely to have missing values due to the occlusion effect, low-reflection objects, etc. Filling holes of depth maps is an important way to meet the demands of depth related computer vision tasks. In this paper, we propose an efficient end-to-end network that takes RGB image and mask of the hole to jointly guide the depth hole-filling. Previous algorithms indistinguishably treat valid pixels and holes, resulting in inaccurate depth values prediction and blurred boundaries. Nevertheless, the proposed algorithm uses the bidirectional attention mechanism which takes the surrounding valid values as the auxiliary information to focus on the process of depth hole-filling from edge to center. The proposed method achieves competitive performance on existing public datasets.

关键词： Bidirectional attention mechanism Depth map Hole-filling RGB guided

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