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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81-90 订阅

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An image retrieval method based on fusion of multiple features 3

An image retrieval method based on fusion of multiple featur...

引用

3rd international conference on advanced algorithms and signal image processing, aasip 2023

作者： Wang, Jiaojuan Dou, Hongbin Guo, Minghan Wang, Binkang School of Information Engineering Lanzhou City University Gansu730070 China Gansu Intellectual Property Protection Center Gansu730030 China School of Computer Science and Artificial Intelligence Lanzhou Institute of Technology Gansu730050 China

ISBN: (纸本)9781510668522

In image retrieval tasks, two main indicators are focused on: Accuracy and efficiency. In general, the more the number of features, the higher the retrieval accuracy but the lower efficiency. Focusing on ensuring retrieval efficiency while improving retrieval accuracy, this paper designs an unsupervised image retrieval system that integrates multiple features. On UKbench, Holidays, UC Merced Land Use, and RSSCN7, the method proposed was validated. On UKbench, compared to methods based on shuffleNetV2, VGG-16 and Resnet18, the method proposed improves N-S by 0.1882, 0.2499, and 0.1985 respectively, while saving retrieval time by 0.0115s. On Holidays, compared to methods based on shuffleNetV2, VGG-16 and Resnet18, the method proposed improves MAP by 7.11%, 9.05%, and 7.27% respectively, while saving retrieval time by 0.0021s. On UC Merced Land Use, compared to methods based on shuffleNetV2, VGG16 and Resnet18, the method proposed improves accuracy by an average of 3.31%, 11.84%, and 6.29% respectively, while saving retrieval time by 0.0007s. On RSSCN7, compared to methods based on shuffleNetV2, VGG-16 and Resnet18, the method proposed improves accuracy by an average of 2.19%, 9.19%, and 7.18% respectively, while saving retrieval time by 0.0002s. The experimental results show that the proposed method can effectively improve retrieval accuracy and to some extent improve retrieval efficiency © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Land use

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Attention-based feature enhanced dehazing network

Attention-based feature enhanced dehazing network

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2021 international conference on advanced algorithms and signal image processing, aasip 2021

作者： Cheng, Yuanshun Tan, Anhui Yang, Chuansheng Yang, Yueting Wang, Chao Tianfu College of SWUFE Sichuan Mianyang621000 China School of Information Engineering Zhejiang Ocean University Zhejiang Zhoushan316022 China Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province Zhejiang Zhoushan316022 China School of Mathematics and Statistics Beihua University Jilin Jilin132013 China

Presence of haze in images obscures underlying information, which is undesirable in applications requiring accurate environment information. To recover such an image, a dehazing algorithm should enhance the feature information of the background while weakening the feature information of haze. In this paper, we propose an end-to-end attention-based feature enhanced dehazing network (AEDNet), which integrates enhancement strategy and attention mechanism, to achieve haze removal. The network is based on U-Net, which has the advantages of retaining information, obtaining multi-scale features and so on. In the training of the network, pixel loss and perceptual loss are used to preserve feature information and improve the overall quality of results. The extensive evaluation shows that the proposed model performs significantly better than previous dehazing methods on various benchmarks. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： image enhancement

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MULTI-SCALE MODEL DRIVEN SINGLE image DEHAZING

MULTI-SCALE MODEL DRIVEN SINGLE IMAGE DEHAZING

引用

IEEE international conference on image processing (ICIP)

作者： Li, Zhengguo Shu, Haiyan Inst Infocomm Res SRO Dept 1 Fusionopolis Way Singapore 138632 Singapore

ISBN: (纸本)9781665441155

Model driven single image dehazing was widely studied due to its broad applications. It is challenging to prevent noise from being amplified in sky region for the model driven dehazing algorithms. In this paper, a new multi-scale hazy image model is first built up by using the Laplacian pyramid of hazy image and the Gaussian pyramid of transmission map. A novel multi-scale dehazing algorithm is then proposed on top of the model to address the problem. Different haze removal and noise reduction approaches are applied to restore the scene radiance at different levels of the pyramid. The resultant pyramid is collapsed to restore a haze-free image. Experiment results demonstrate that the proposed algorithm outperform state of the art dehazing algorithms and the noise is indeed prevented from being amplified in the sky region.

关键词： Maximum likelihood detection Laplace equations image edge detection conferences Noise reduction Nonlinear filters Filtering algorithms

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New Ultrasound image Watermarking Enhancement algorithm for cardiovascular disease 6

New Ultrasound Image Watermarking Enhancement algorithm for ...

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

作者： Kumar, Prashant Gupta, Sachin Ratan, Rajeev MVN University Haryana Palwal India

ISBN: (纸本)9781665425520

The primary goal of this article is to implement a new space-frequency-domain picture enhancing method. algorithms often have low contrast, although algorithmic algorithms solve this issue. After that, the heuristic image search method is employed to search for the picture of the cost matrix. A study published in the journal Computer Assisted Tomography concluded that when an image-processing technique called a spatial-frequency-domain image ultrasound imaging algorithm is used, ultrasound image watermarking of cardiovascular disease have improved contrast and sharpness, leading to better middle-edge visibility, increased detection accuracy, and improvement in ultrasound of cardiovascular disease. Also, the sharpness of the image border is kept intact. A study published in e studied the effectiveness of the ultrasound imaging method, which is based on spatial frequency domain image enhancement, in clinical applications. More energy efficient yields more grain, sharper, more contrast, and more information. © 2021 IEEE.

关键词： image watermarking

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Low-light image enhancement based on deep convolutional neural networks

Low-light image enhancement based on deep convolutional neur...

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2021 international conference on signal image processing and Communication, ICSIPC 2021

作者： Yong, Chen Dong, Chen The Key Laboratory of Industrial Internet of Things and Network Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China

ISBN: (数字)9781510645417

ISBN: (纸本)9781510645400

A reference-free low-illumination image enhancement method based on deep convolutional neural networks is proposed to address the problem that low-illumination image enhancement algorithms do not take into account noise suppression while achieving detail enhancement. First, the illumination and reflection components are extracted from the input lowillumination image based on Retinex theory, and optimised separately, and then the optimised illumination and reflection components are multiplied to obtain the enhanced image. loss to update the network parameters. The experimental results show that our algorithm can effectively enhance the contrast and brightness of low-illumination images compared to existing mainstream algorithms, while maintaining the naturalness of the images. © 2021 SPIE.

关键词： image enhancement

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Performance Evaluation of Speech Enhancement of Single Acoustic signal Referring to image Information 5

Performance Evaluation of Speech Enhancement of Single Acous...

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

作者： Matsumoto, Mitsuharu Univ Electrocommun Dept Informat 1-5-1 Chofugaoka Chofu Tokyo 1828585 Japan

ISBN: (纸本)9781665424257

This paper presents performance evaluation of speech enhancement of an acoustic signal referring to image information. In recent years, we often see smart phones and tablets in everyday life. Smart phones and tablets have a camera and a microphone. Although many speech enhancement techniques use only the audio information from microphones, it is considered that visual information from a camera is also helpful to enhance the speech. Although the frame rate of the normal movie is very low compared to the sampling frequency of the audio signal, it is useful if it is adequately used. We investigated the performance depending on the parameters and confirmed its effectiveness through the experiments.

关键词： Vision-referential speech enhancement Mask information Smart phone Binary mask

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Edge detection algorithm of low SNR image based on mixed filtering

Edge detection algorithm of low SNR image based on mixed fil...

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2021 IEEE international conference on signal processing, Communications and Computing, ICSPCC 2021

作者： Qi, Tang Yi-Xuan, Sun Ke-Xin, Zhou Wen-Tian, Wang Xi'An University of Posts Telecommunication Xi'an China

ISBN: (纸本)9781665429184

Aiming at the available edge detection algorithms can not effectively extract the edge information for low SNR image, a new edge detection algorithm for low SNR image based on mixed filter is proposed in this paper. Which using a mixed filter to achieve the effects of edge protection and denoising, and then acquires the image edge by high effective differential operators. Experimental results show that under the interference of different concentrations of salt-And-pepper noise, the proposed algorithm can not only filter out noise better, but also retain more edge information and improve edge connectivity than the available edge detection algorithms. © 2021 IEEE.

关键词： Edge detection

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A Comparison between AttnGAN and DF GAN: Text to image Synthesis 3

A Comparison between AttnGAN and DF GAN: Text to Image Synth...

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3rd international conference on signal processing and Communication (ICPSC)

作者： Sumi, Philo Sindhuja, S. Sureshkumar, S. Bannari Amman Inst Technol Dept Comp Sci & Engn Sathyamangalam India

ISBN: (纸本)9781665428644

Nowadays conversion from text to high resolution image is a challenging task due to its wide variety of application area. For text to image conversion almost all systems use Generative Adversarial Networks as the basic part of the system and GAN guarantees semantic consistency between the text input and the generated image output. In this paper we are comparing two algorithms that is used for generating image from text. The first algorithm is the AttnGAN and the second one is the DF-GAN. AttnGAN builds on top of StackGAN by using attention network which allows it to capture word level information along with the broader sentence level information. The second algorithm is the DF-GAN, which uses single generator and discriminator model to synthesize high resolution images and also uses Matching-Aware Gradient Penalty (MA-GP) to get real images with real description. The model contains a Deep text-image Fusion Block ( DFBlock) to generate image features from text. Both algorithms work efficiently for image generation from text but DF-GAN generates the perfect output than AttnGAN. The AttnGAN always focus on the textual part to generate output image but DF-GAN also focuses on background of image.

关键词： AttnGAN DF GAN BLSTM CNN

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EMPIRICALLY ACCELERATING SCALED GRADIENT PROJECTION USING DEEP NEURAL NETWORK FOR INVERSE PROBLEMS IN image processing

EMPIRICALLY ACCELERATING SCALED GRADIENT PROJECTION USING DE...

引用

IEEE international conference on Acoustics, Speech and signal processing (ICASSP)

作者： Lee, Byung Hyun Chun, Se Young UNIST Grad Sch AI Seoul South Korea Seoul Natl Univ INMC Dept ECE Seoul South Korea

ISBN: (纸本)9781728176055

Recently, deep neural networks (DNNs) have shown advantages in accelerating optimization algorithms. One approach is to unfold finite number of iterations of conventional optimization algorithms and to learn parameters in the algorithms. However, these are forward methods and are indeed neither iterative nor convergent. Here, we present a novel DNN-based convergent iterative algorithm that accelerates conventional optimization algorithms. We train a DNN to yield parameters in scaled gradient projection method. So far, these parameters have been chosen heuristically, but have shown to be crucial for good empirical performance. In simulation results, the proposed method significantly improves the empirical convergence rate over conventional optimization methods for various large-scale inverse problems in image processing.

关键词： scaled gradient projection deep neural network iterative algorithm convergence

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advanced deep learning enhancement algorithm based on retinex model guidance

Advanced deep learning enhancement algorithm based on retine...

引用

2021 international conference on Optical Instruments and Technology: Optoelectronic Imaging/Spectroscopy and signal processing Technology

作者： Zhang, Hangying Cao, Liangcai State key Laboratory of Precision Testing Technology and Instruments Department of Precision Instruments Tsinghua university Beijing100084 China

ISBN: (纸本)9781510655676

Traditional Retinex model-based image enhancement methods require careful design of constraints and parameters to handle this highly ill-conditioned decomposition. With the advancement of deep learning algorithms, low-light image enhancement has also achieved deep processing. However, image enhancement based on the RGB color space model is prone to color distortions when enhancing images under the influence of the correlation of the three primary colors of RGB. In this report we apply the HSV color space technique to a Retinex-based network model. Simulations and experiments show that using HSV space-improved deep neural networks can effectively avoid the color distortion problem. © 2022 SPIE.

关键词： image enhancement

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