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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 691 条记录，以下是271-280 订阅

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Multispectral image Compression Algorithm Based on Sliced Convolutional LSTM 10th

Multispectral Image Compression Algorithm Based on Sliced Co...

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10th international conference on Communications, signal processing, and Systems, CSPS 2021

作者： Wang, Kang Zhang, Ning Hu, Kedi Cao, Tongbo College of Astronautics Nanjing University of Aeronautics and Astronautics Nanjing210016 China Xian710065 China

ISBN: (纸本)9789811903854

The multispectral imaging which are used for remote sensing imaging has a large amount of data, so this paper proposed a deep learning method which is based on sliced convolutional LSTM for multispectral image compression. Compared with other algorithms, the proposed algorithm further compresses the multispectral images by considering the similarity between the spectra and removing the inter-spectral redundancy. The proposed algorithm is based on end to end framework which is consist of encoder, decoder, entropy coding and quantizer. In experiments, the PSNR of proposed model is compared with that of JPEG2000 to evaluate the performance of our algorithm at several different bit rates. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Convolution

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Boundary Accuracy of Interactive Segmentation Methods on Various Distorted images 11th

Boundary Accuracy of Interactive Segmentation Methods on Var...

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11th international conference on Robotics, Vision, signal processing and Power Applications, RoViSP 2021

作者： Rahmatullah, Bahbibi Mahamud, Siti Tasnim Tamrin, Khairul Fikri Samuri, Suzani Mohd Perak Tanjung Malim35900 Malaysia Sarawak Kota Samarahan94300 Malaysia

ISBN: (纸本)9789811681288

Quality of image is an important factor to be considered in coming up with effective segmentation algorithms. As images go through several different stages of processing such as acquisition, compression, transmission, storage, and reproduction, these digital images are easily exposed to various types of degradation leading to the deterioration of image quality. Many state-of-art segmentation methods are not prepared to handle the various level of degradation in visual quality. This paper aims to address this issue by comparing and analyzing the performance of two types of interactive segmentation methods on images with common types of distortion artifacts. The well-known Jaccard index for measuring boundary accuracy is used for evaluation of the segmentation output. The experimental results revealed interesting and unique findings of segmentation accuracy on different levels of distorted images. This indicates that the image quality plays an important role in segmentation accuracy and the need to consider the distortion effect towards achieving higher accuracy in segmentation. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： image segmentation

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1st international Scientific and Practical conference on Information Technologies and Intelligent Decision Making Systems, ITIDMS 2021

1st International Scientific and Practical Conference on Inf...

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1st international Scientific and Practical conference on Information Technologies and Intelligent Decision Making Systems, ITIDMS 2021

ISBN: (纸本)9783031213397

The proceedings contain 13 papers. The special focus in this conference is on Information Technologies and Intelligent Decision Making Systems. The topics include: Tone image processing with Discrete Data Structure;the Concept of Client-Server Architecture for Remote Control of a Distributed Knowledge Base;experimental Study of Russian-Language News Text Categorization Performance Using Machine Learning algorithms;experimental Evaluation of the Efficiency of Compression of Files by Fractal-Spectral Codec;an Intelligent Decision Support System for Solving Complex Territorial Planning Problems;fault Tolerance of Distributed Worker Processes in Corporate Information Systems and Technologies;functioning of the Thermal Memory Cell;using Data Mining Technology in Monitoring and Modeling the Epidemiological Situation of the Human Immunodeficiency Virus in Kazakhstan;information Technology and Artificial Intelligence in Improving of Center Pivot Irrigation Control;KOA Pathology Screening Using Multi-channel VAG signal Fusion Method;prioritization of Distributed Worker Processes Based on Etcd Locks.

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LOSSY EVENT COMPRESSION BASED ON image-DERIVED QUAD TREES AND POISSON DISK SAMPLING

LOSSY EVENT COMPRESSION BASED ON IMAGE-DERIVED QUAD TREES AN...

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IEEE international conference on image processing (ICIP)

作者： Banerjee, Srutarshi Wang, Zihao W. Chopp, Henry H. Cossairt, Oliver Katsaggelos, Aggelos K. Northwestern Univ Evanston IL 60208 USA

ISBN: (纸本)9781665441155

Event cameras have provided new opportunities for tackling visual tasks under challenging scenarios over conventional RGB cameras. However, not much focus has been given on event compression algorithms. The main challenge for compressing events is its unique asynchronous form. To address this problem, we propose a novel event compression algorithm based on a quad tree (QT) segmentation map derived from the adjacent intensity images. The QT informs 2D spatial priority within the 3D space-time volume. In the event encoding step, events are first aggregated over time to form polarity-based event histograms. The histograms are then variably sampled via Poisson Disk Sampling prioritized by the QT based segmentation map. Next, differential encoding and run length encoding are employed for encoding the spatial and polarity information of the sampled events, respectively, followed by Huffman encoding to produce the final encoded events. Our algorithm achieves greater than 6x higher compression compared to the state of the art.

关键词： Lossy Event Compression Poisson Disk Sampling Quad tree segmentation

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ICMSSP 2021 - 2021 6th international conference on Multimedia Systems and signal processing

ICMSSP 2021 - 2021 6th International Conference on Multimedi...

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6th international conference on Multimedia Systems and signal processing, ICMSSP 2021

ISBN: (纸本)9781450390378

The proceedings contain 11 papers. The topics discussed include: comparative study on image classification algorithm based on dimensionality reduction technologies and convolutional neural networks;MergeNet: single high dynamic range image reconstruction method;image aesthetic assessment based on emotion-assisted multi-task learning network;pyramid attention generative adversarial network for image compressed sensing;immersive teleconferencing with efficient implementation of fast frequency domain adaptive acoustical echo cancellation;a method based on LSTM network for detection of abnormal daily electricity;research on collaborative detection and location method of infrared and radar aircraft based on federated filter;and analysis of deep anomaly detection algorithms.

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Common Carotid Artery Ultrasound image Enhancement Based on Fuzzy Set Theory and Phase Asymmetry Metric 4

Common Carotid Artery Ultrasound Image Enhancement Based on ...

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4th international conference on Information Communication and signal processing, ICICSP 2021

作者： Wang, Kun Zhang, Yufeng Li, Zhiyao Lang, Xun He, Bingbing School of Information Science and Engineering Yunnan University Department of Electronic Engineering Yunnan Kunming China

ISBN: (纸本)9781665407571

Carotid ultrasound images can be used for computer-aided diagnosis of atherosclerosis. However, the low contrast and blurred edges in ultrasound images can reduce the accuracy of the diagnosis. In this study, an image enhancement algorithm is proposed for common carotid artery (CCA) ultrasound images. First, the CCA ultrasound images are normalized. Next, the normalized images are fuzzified by using the S-function. Then, the fuzzified images are enhanced based on non-linear transform. After enhancement, the images are transferred from the fuzzy domain to the spatial domain by using the inverse function. Finally, an edge enhancement method based on the phase asymmetry (PAS) metric is proposed for CCA ultrasound images. The final results indicate that the proposed method has outstanding performance as compared with other advanced methods. © 2021 IEEE.

关键词： image enhancement

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Automatic Detection of Cowpea leaves Using image processing and Inception-V3 Model of Deep Learning 6

Automatic Detection of Cowpea leaves Using Image Processing ...

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

作者： Choudhary, Vijaya Guha, Paramita Tripathi, Kuldeep Mishra, Sunita Ghaziabad201002 India CSIR- Central Scientific Instruments Organization Delhi Centre India ICAR- National Bureau Of Plant Genetic Resources Delhi India

ISBN: (纸本)9781665425520

India is an agriculture-based country, and most of the population depends on agriculture for livelihoods. Cowpea plays a vital role to maintain healthy life because of its nutritious parameters. However, there is an urgent need to implement new technologies using Artificial Intelligence to enhance the productivity of crops and mitigate the cost, effort and loss of the agronomist. We have proposed a model based on deep learning algorithms to identify Cowpea leaves. For experiments, images were captured from the ICAR-NBPGR farm. We use TensorFlow and Keras platform under the umbrella of Deep Learning. Such methodology permits us 1) reorganization of the cowpea leaves based on image classification and 2) to estimate their weight. Inception model is type of application utilizes CNN based architecture to complete problems related to either binary or multiclass classification, that will again moderate by using transfer learning technique. We have initiate model for binary classification of Cowpea leaves with other leaves (Mango). © 2021 IEEE.

关键词： Convolutional neural networks

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Fast Low-light image Enhancement Algorithm Based on Fusion 6

Fast Low-light Image Enhancement Algorithm Based on Fusion

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

作者： Guo, Junjie Li, Zhengping Xu, Chao Feng, Bo AnHui University AnHui Engineering Laboratory of Agro-Ecological Big Data School of Electronics and Information Engineering HeFei China

ISBN: (纸本)9780738133737

Low-light images generally exist in various situations, and the existing low-light image enhancement algorithms are poor in generality and have high computational complexity, and the comfort of the enhanced image is not satisfactory. This paper proposes a fast low-light image enhancement algorithm based on fusion. First, transform the passing space to HSV space to extract the V component. Then, according to the influence of Weber-Fechner's law on human visual senses, and effectively combining the characteristics of low-light images, a global adaptive brightness transformation function is constructed, and this function generates the first enhanced image. Then use CLAHE to increase the local contrast and generate a second enhanced image. Finally, an image fusion strategy is adopted to extract image details to fuse the image effectively. The proposed algorithm is fast and straightforward, can effectively improve the quality of low-light images, and better preserve its naturalness. Experimental results show that the proposed algorithm has achieved good results both subjectively and objectively. © 2021 IEEE.

关键词： image enhancement

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Research on Endoscopic image Enhancement Algorithm Based on Contrast Fusion 6

Research on Endoscopic Image Enhancement Algorithm Based on ...

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

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

ISBN: (纸本)9780738133737

image enhancement can improve doctors' perception of gastrointestinal tissues and blood vessels. This paper introduces an image enhancement method for medical endoscopy, which includes three stages: (1) improved contrast enhancement algorithm, using multiple iterative sharpening mask to enhance the edge contour of gastrointestinal tissues and blood vessels;(2) improved limiting threshold of limiting contrast adaptive histogram equalization (CLAHE);(3) improved contrast image fusion to preserve the good characteristics of improved contrast enhancement algorithm and improved CLAHE. The proposed method is applied to large data sets of low contrast white light endoscopes. The experimental results show that the endoscopic image enhancement algorithm based on contrast fusion is a feasible method to solve the defects between different image enhancement algorithms, because the image fusion results can effectively reduce the defects of contrast enhancement algorithm and CLAHE compared with the original image, such as detail loss, local contrast loss and pixel value loss. © 2021 IEEE.

关键词： image enhancement

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A Secure Wavelet based Watermarking Approach using Psycho-Visual Redundancy in image 7

A Secure Wavelet based Watermarking Approach using Psycho-Vi...

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7th international conference on advanced Computing and Communication Systems, ICACCS 2021

作者： Sinha, Ashish Panda, Jeebananda Delhi Technological University Technology Student Delhi India

ISBN: (纸本)9781665405201

The principal requirements of any digital watermarking algorithm are imperceptibility, robustness, security and capacity of the watermark [2], [9]. Imperceptibility and robustness are inherently conflicting in nature. Over numerous trials of digital watermarking of multimedia, it has been found that embedding a watermark with high strength also decreases its obscurity and makes the watermark more prone to detection. On the other hand, a watermark embedded with a low strength improves the imperceptibility but causes degradation of robustness against signal processing, geometric and feature distortive attacks. This paper proposes a secure approach for watermarking using the image Partitioning approach, which exploits the psycho-visual redundancy in the image to embed the watermark. Using the chaotic scrambling based Arnold Transform, watermark is first scrambled and then embedded in the sub-band of the image obtained using the Discrete Wavelet Transform and characterized by the lowest frequency. This improves the security as well as enhances the imperceptibility of the watermark, without significant deviation in visual appearance of the watermarked image from the cover image. Further, frequency domain embedding leads to better robustness and stability. The method is used to perform watermarking of grayscale images and performs well when subjected to common distortions, geometric, order-statistic filtering and signal processing attacks. This was determined by calculating the Peak signal to Noise Ratio of the watermarked cover image and the retrieved watermarks and the Normalized Cross-Correlation of the embedded and extracted watermarks. © 2021 IEEE.

关键词： Discrete wavelet transforms

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