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image Sharpness Control in Modern Television systems

Image Sharpness Control in Modern Television Systems

引用

2020 ieee international conference on Problems of Infocommunications Science and technology, PIC S and T 2020

作者： Gofaizen, Oleg Osharovska, Olena Patlayenko, Mikola Pyliavskyi, Volodymyr Kiiko, Svitlana Solodka, Valentyna O.S. Popov Odessa National Academy of Telecommunications Department of Television and Sound Broadcasting Odessa Ukraine

ISBN: (纸本)9781728191775

The article is devoted to establishing a connection between the subjective assessment of the TV images quality and the generalized criterion of definition in two dimensions. In modern practice in television definition is characterized by the number of active scan lines and the number of active picture elements per line. It should be taken into account that the achievable image definition is limited by diffraction distortions of the lens and blurring due to the finite dimensions of the 'light-to-signal' and 'signal-to-light' conversion elements of the matrix sensor camera and playback display screen. The question of what should be the MTF of an image processing system used to improve definition in two dimensions is relevant, based on the compromise between the attainable level of definition and the interfering effect of edging in the image arising as a result of excessive emphasis on image details. The article is devoted to answering this question, but the experimental data presented in it are focused on solving the more general problem of establishing the relationship between image quality and definition in two dimensions for the general case. In the experiments, to vary the resulting definition, a controlled two-dimensional corrector was used in the form of a digital filter with circular symmetry MTF. It was provided for the possibility of blurring the image by limiting the frequency band and correcting definition by using a corrector with a rise that varies according to the cosine-square law so that the maximum was achieved at a frequency equal to half the spatial Nyquist frequency, i.e. the number of scan lines per frame height. The relative volume under the two-dimensional MTF of the TV path 'from light to light' was used as a generalized criterion for definition. © 2020 ieee.

关键词： image quality

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S-CIEL *a*b* based Quality Assessment of images Restored from Non-Gaussian-Noise-Corrupted-images and Non-Linear-Bilateral-Kernel based Restoration

S-CIEL *a*b* Based Quality Assessment of Images Restored fro...

引用

ieee international WIE conference on Electrical and Computer Engineering (WIECON-ECE)

作者： Prabhakar Rao Barre Shraddha Prasad Vinay Kumar Pamula Raja Rao Chatla Mahendra Babu Duddu John Paul Pulipati Dept. of Electronics and Electrrical Engineering Jharkhand Rai University Ranchi India Faculty of Science and Engineering Jharkhand Rai University Ranchi India Dept. of Electronics and Communications Engineering Jawaharlal Nehru Technological University Kakinada India Board of Practical Training (Eastern Region) Kolkata India Bharat Sanchar Nigam Limited Hyderabad India Dept.of Electronics and CommunicationsEngineering Ellanki College of Engineering Hyderabad India

ISBN: (数字)9798331535476

ISBN: (纸本)9798331535483

Most widely used image-quality-assessment- metrics viz., Cumulative Minimum-Mean-Square-Error (CMMSE) and Cumulative Peak-signal-to-noise-ratio (CPSNR) do not satisfactorily measure the quality of image-restoration. As it is an observed empirical fact amongst the fraternity of researchers that a difference of ten or even twenty percentage in SNR may not at all translate into any difference in the perceivable image quality. And, by some construction, images that have similar PSNR but of drastically different attributes can conceivably created. This challenge is addressed empirically in this study by using S-CIEL*a*b* image-assessment-quality-metrics. Of course, spatially extended CIEL*a*b* (S-CIEL*a*b*) is primarily used to represent colors numerically and to calculate the color differences for the scholarly reason that the human vision can perceive millions of color differences; but no technology can meaningfully replicate the ability of human eye as closer as the CIEL*a*b* can perform. Another unique feature of the research study is that the restoration is achieved from the non-Gaussian-noise-corrupted-natural images. It is an observed fact that linear filters blur the restored image; here in this investigative study the non-linear-bilateral filter technique is implemented in order to establish the superior performance of the said assumptions and objectives of the study. The standard datasets are used for carrying the experimentation.

关键词： Measurement image quality Filters image color analysis image restoration Quality assessment Standards signal to noise ratio

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Rock Thin-Sectionimage Classification based on Residual Neural Network 6

Rock Thin-SectionImage Classification based on Residual Neur...

引用

6th ieee international conference on Intelligent Computing and signal Processing, ICSP 2021

作者： Guojian, Cheng Peisong, Li Xi'an Shiyou University School of Computer Science Xi'an ShaanXi China

ISBN: (纸本)9780738143705

When classifying rock slices, due to the small particle size of the rock slices, the classification is difficult. When manual methods are used for identification, the efficiency is low and subject to subjective factors. Therefore, this paper proposes a rock based on residual network The method of classifying granular images. This method uses the ResNet50 and ResNet101 models in the residual network to realize the automatic extraction of image features, and establishes a classifier to realize the classification based on the size of the rock slice image. This experiment uses 10,000 rock slice images obtained from the Ordos Basin, and uses 8,000 of them as the training set The residual network model is used for training, and then another 2,000 images are used to test the model. The experimental results show that two networks The accuracy of the classification results of the structure in the test set reached 90.24% and 91.63%. By using the residual network model to classify based on the rock slice image, an efficient and accurate classification effect can be obtained. © 2021 ieee.

关键词： image classification

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Research on Computer Aided French Audiovisual Intelligence System

Research on Computer Aided French Audiovisual Intelligence S...

引用

Sensors, Electronics and Computer Engineering (ICSECE), ieee international conference on

作者： Fengyi Sun Xianda School of Economics and Humanities Shanghai International Studies University Shanghai China

ISBN: (数字)9798350373646

ISBN: (纸本)9798350373653

Aiming at the existing problems in French education, a set of intelligent French teaching system with independent intellectual property rights is designed and implemented. based on cloud computing, the system realizes the effective integration of various network resources distributed between servers and users. It effectively improves the query efficiency of network resources. The system assesses and evaluates students' knowledge and learning outcomes based on their cognitive and knowledge acquisition preferences. This project intends to study the pseudo-color display based on C# programming. Through nonlinear transformation, the correspondence between spectral intensity and color is constructed to achieve the purpose of pseudo-color display. It is applied to the display of language graph and the interface design of speech signal. In addition, the function of sound playback is added to the display of the spectrum, so that it can be reproduced in a “visual” way. This algorithm has the characteristics of simple program, flexible man-machine interface and small demand for instruments. It can be done on a normal PC. Through simulation and verification, the method has a good effect. Finally, the proposed algorithm is verified by computer simulation experiment.

关键词： Visualization image color analysis Education Transfer functions User interfaces Sensor systems and applications Servers Logic Speech processing Programming profession

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Access control method using electromyogram signal for consumer electronics system security

Access control method using electromyogram signal for consum...

引用

ieee international conference on Consumer Electronics-Asia (ICCE-Asia)

作者： Kim, Jin Su Kim, Min Gu Pan, Sung Bum Chosun Univ IT Res Inst Gwangju South Korea Chosun Univ Interdisciplinary Program IT Bio Convergence Syst Gwangju South Korea

ISBN: (纸本)9781665408578

As the internet of Things (IoT) technology develops, Consumer Electronics (CE) is equipped with network function, providing convenience to users. However, since they are connected to each other by network, hacking allows access to a variety of devices, and existing user recognition methods used to control the CE information has vulnerable security. In this paper, we proposed a CE access control method using Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) based Electromyogram (EMG) signal. EMG signal is preprocessed with a digital filter and then converted into a spectrogram, and the user is recognized using the designed CNN-LSTM. To verify the possibility of proposed CE access control method, the experiment was performed using Ninapro DB2. As a result of the experiment, twenty users showed 99.2% accuracy. In addition, experiment result showing 1.1% higher performance compared to the existing user recognition method using CNN. Therefore, possibility of CE access control using EMG signal of user was confirmed.

关键词： Consumer electronics Access control method User recognition Electromyogram signal

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Quantum-Resistant Secure Data Provenance in internet of Vehicles

Quantum-Resistant Secure Data Provenance in Internet of Vehi...

引用

Symposium of image, signal Processing, and Artificial Vision (STSIVA)

作者： Anuj Nepal Robin Doss Frank Jiang Deakin Cyber Research and Innovation Centre (Deakin Cyber) Deakin University Geelong Australia

ISBN: (数字)9798350363203

ISBN: (纸本)9798350363210

internet of Vehicles (IoV) network facilitates an advanced vehicular communication landscape that integrates various infrastructures to enhance vehicle-to-everything (V2X) interactions. However, the advancement of quantum computing presents substantial risks to conventional cryptographic protocols essential for data security, integrity, and confidentiality. This paper introduces an advanced framework incorporating quantum-resistant cryptographic algorithms within the IoV's secure data provenance (SDP) protocols. We leverage robust post-quantum cryptographic (PQC) methods, specifically the Falcon-512 lattice-based signature scheme, alongside Verifiable Credentials (VCs) to ensure data integrity, source authentication, and privacy against potential quantum threats. The integration process, security, and performance of our framework are thoroughly analyzed. The analysis demonstrates its resilience against classical and quantum attacks, making it a viable solution to secure IoV communications in the quantum era.

关键词： Quantum computing Solids Safety Security Cryptography Reliability Vehicle-to-everything Resilience internet of Vehicles Cryptographic protocols

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Semantic Graph Embedded Energy Minimization Learning for Scene Graph Generation

Semantic Graph Embedded Energy Minimization Learning for Sce...

引用

international conference on Acoustics, Speech, and signal Processing (ICASSP)

作者： Jinghang Chen Chi Zhang Yuehu Liu Le Wang Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an China National Engineering Research Center for Visual Information and Applications National Key Laboratory of Human-Machine Hybrid Augmented Intelligence

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

The performance of current scene graph generation models is affected by training with cross-entropy loss, exacerbating the problem of prediction bias stemming from biased training data. Energy-based model adopts a learning method for joint image and scene graph to alleviate this challenge. However, this method only focuses on the visual features of images, neglecting the rich relation information contained in the semantic space. To address this issue, we innovatively employ powerful pre-trained large models to realize a simple yet effective semantic graph embedded energy minimization framework for the SGG task. Specifically, we use large models to generate image descriptions and extract relation triplets, which are then transformed into semantic graphs with entities as nodes and relations as edges. Moreover, by mapping these graphs into the same space using GNN to learn the minimal energy value, our approach enables SGG model to learn structural information in both semantic and visual spaces. We validate the effectiveness and efficiency of our method on the SGG benchmark Visual Genome dataset. Compared with prevailing models and EBM, we achieve a significant performance improvement of up to 2.99% and 2.24%, respectively.

关键词： Training Learning systems Visualization image edge detection Semantics Training data signal processing Predictive models Minimization Speech processing

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VAC-UNet: Visual Attention Convolution U-Net for 3D Medical image Segmentation

VAC-UNet: Visual Attention Convolution U-Net for 3D Medical ...

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Medical Artificial Intelligence (MedAI), ieee international conference on

作者： Tianfeng Ke Xiaofei Yang Xiaofeng Zhang Weijia Cao Chunfeng Li Sihuan Li State Key Laboratory of Internet of Things for Smart City University of Macau Macau China School of Electronic and Communication Engineering Guangzhou University Guangzhou China Shenzhen Key Laboratory of Internet Information Collaboration Harbin Institute of Technology (Shenzhen) Shenzhen China Aerospace Information Research Institute Chinese Academy of Sciences Beijing China School of Information Engineering Shenzhen Open University Shenzhen China

Deep learning-based methods have achieved significant success in medical image segmentation. However, the intrinsic locality of convolutional operations limits the learning of global semantic information. In this paper, we propose a novel method, namely VAC-UNet that is a convolutional transformer U-Net architecture for enhanced global representation. Specially, we introduce a novel Visual Attention Convolution (VAC) block integrating transformers and CNNs for joint local-global feature learning. VAC blocks replace standard convolutions in the encoder-decoder backbone. Asymmetric application on encoders improves localization. Additionally, we design Visual Attention Gates using learned convolution filters to suppress irrelevant regions in skip connections. Finally, we evaluated VAC-UNet on two medical image segmentation tasks against state-of-the-art methods. The results demonstrate VAC blocks effectively capture global context while maintaining local precision. The visual attention improves feature propagation for better segmentation.

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Semantic NOMA Satellite Communications based on Knowledge Graph

Semantic NOMA Satellite Communications Based on Knowledge Gr...

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3rd international conference on internet of Things, Communication and Intelligent technology, IoTCIT 2024

作者： Lai, Haiguang Wei, Wu Wang, Xi Zhu, Bangbing Shen, Jinhai Sheng, Mingyue Wang, Xiaoming Nanjing Cowave Communication TechnoIogy Co. Ltd Nanjing China Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9789819627660

Satellite communications transmit data and information by satellites to achieve global communication connectivity. We propose a semantic Non-orthogonal multiple access (NOMA) satellite communication transceiver based on knowledge graph, which uses triples as semantic symbols to extract semantic information. The pre-trained model is fine-tuned to reconstruct the text. In addition, a successive interference cancellation method MeanSIC based on subtractive mean interference is proposed to reduce inter user interference and achieve user signal separation. The experiment result shows that the proposed system can not only reduce the communication resources required to transmit the same data, but also effectively reduce interference between users. Our channel reconstruction scheme ensures high reliability and facilitates signal recovery. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： image reconstruction

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A Hybrid Joint Source-Channel Coding Scheme for Mobile Multi-Hop Networks

A Hybrid Joint Source-Channel Coding Scheme for Mobile Multi...

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ieee international conference on Communications (ICC)

作者： Chenghong Bian Yulin Shao Deniz Gündüz Department of Electrical and Electronic Engineering Imperial College London Department of Electrical and Computer Engineering State Key Laboratory of Internet of Things for Smart City University of Macau Macau S.A.R.

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

We propose a novel hybrid joint source-channel coding (JSCC) scheme for robust image transmission over multihop networks. In the considered scenario, a mobile user wants to deliver an image to its destination over a mobile cellular network. We assume a practical setting, where the links between the nodes belonging to the mobile core network are stable and of high quality, while the link between the mobile user and the first node (e.g., the access point) is potentially time-varying with poorer quality. In recent years, neural network based JSCC schemes (called DeepJSCC) have emerged as promising solutions to overcome the limitations of separation-based fully digital schemes. However, relying on analog transmission, DeepJSCC suffers from noise accumulation over multi-hop networks. Moreover, most of the hops within the mobile core network may be high-capacity wireless connections, calling for digital approaches. To this end, we propose a hybrid solution, where DeepJSCC is adopted for the first hop, while the received signal at the first relay is digitally compressed and forwarded through the mobile core network. We show through numerical simulations that the proposed scheme is able to outperform both the fully analog and fully digital schemes. Thanks to DeepJSCC it can avoid the cliff effect over the first hop, while also avoiding noise forwarding over the mobile core network thank to digital transmission. We believe this work paves the way for the practical deployment of DeepJSCC solutions in 6G and future wireless networks.

关键词： image coding image communication Wireless networks Simulation Noise Semantics Spread spectrum communication

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