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distributed Systems, Computer Networks and Cybersecurity (ICDSCNC), International Conference on

作者： Ramy Riad Al-Fatlawy P. Raviprakash Gummagatta Yajaman Vybhavi Sripelli Jagadish S Meenakshi Sundaram Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Malla Reddy Engineering College for Women (UGC-Autonomous) Hyderabad India Department of CSE Gokaraju Rangaraju Institute of Engineering and Technology Bachupally Hyderabad India School of Computer Science & Artificial Intelligence SR University Warangal India Department of CSE Nitte Meenakshi Institute of Technology Bengaluru India

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

Satellite image classification for land cover involves determining high-resolution imagery to recognize and classify various types of land covers. This process assists in monitoring forest health, managing resources, and assessing biodiversity effectively. However, accurately classifying images for land cover is difficult because of diverse and complex nature of forest environments and varying image qualities. In this research, the Convolutional Neural Network with Huber Loss Function (CNN-HLF) is proposed to classify the satellite images accurately for landcover mapping in forest ecosystem. The CNN-HLF effectively manage the variability and complexity of forest environments which improves the performance of land cover. Initially, the Eurosat dataset is used to determine the CNN-HLF performance. Resizing and image sharpening is applied to adjust the size and enhance the clarity of features. DenseNet201 is employed for extracting features effectively from pre-processed images. The proposed CNN-HLF achieves a high accuracy of 99.87% using Eurosat dataset compared to existing methods like GoogleNet with pre-processing and Lightweight parallel CNN (LPCNN).

关键词： Training Accuracy Ecosystems Land surface Forestry Feature extraction Stability analysis Robustness Satellite images Convolutional neural networks

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Intelligent image processing based on VPX architecture 8

Intelligent image processing based on VPX architecture

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8th Symposium on Novel Photoelectronic Detection Technology and Applications

作者： Tao, Xin Ou, Weilin He, Wenbo Huazhong Institute of Electro-Optics Wuhan National Laboratory for Optoelectronics Wuhan430074 China

ISBN: (数字)9781510653122

ISBN: (纸本)9781510653115

Multiple bands cameras with high pixel resolution and fast frame rate bring challenges for real-time signal process which is important in monitoring and alerting application. Especially, the deep neural network algorithm which has been applied in practical EO system, requires high parallel computation ability. Thus, the traditional signal processing method in imaging sensor cannot satisfy the novel demands for balancing the capability and consumption. The system based on VPX architecture and all optical signal transmission can provide a promising improvement in computation capability, transmission bandwidth and data transfer capability. In this paper, a novel signal processing system for intelligent computing based on VPX architecture is indicated. Based on the system structure and components indication, the main configuration design is also explained. Especially the thermal deisgn of the full system is explained in details, because the thermal effect and related methods are important in high speed conputation system. The main intelligent signal processing circuit is based on FPGA SOC processor. After introducing the hardware design and scheme, an optimized SSD algorithm is introduced for multi-scales target detection, and the method to applying these algorithms on FPGA chip for real-time compuation is explained. Finally, this method is verified in both visible and IR images, especially for the small target in IR images. The whole design is verified that it can provide a promising solution for high performance and distributed EO imaging system. © 2022 SPIE

关键词： Data transfer

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Detecting and analysing geomorphological structures in images of comet 67P/Churyumov-Gerasimenko using Fourier transform

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MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY 2021年第3期503卷 3449-3459页

作者： Ruzicka, Birko-Katarina Schroeter, Matthias Pack, Andreas Boehnhardt, Hermann Max Planck Inst Sonnensyst Forsch Justus von Liebig Weg 3 D-37077 Gottingen Germany Georg August Univ Gottingen Geowissensch Zentrum Abt Isotopengeol Goldschmidtstr 1 D-37073 Gottingen Germany Max Planck Inst Dynam & Self Org D-37077 Gottingen Germany

We present a method for automatized detection and analysis of quasi-periodic lineament structures from images at pixel precision. The method exploits properties of the images' frequency domain found by using the Fourier transform. We developed this method with the goal of detecting lineament structures in an image of the Hathor cliff of comet 67P/Churyumov-Gerasimenko, which are caused by layerings and furrows in the nucleus material. Using our method, we determined the orientation and wavelength range of these structures. The detected layering edges have similar orientations and spatial separations of 9-20 m, and are ubiquitous throughout the image. We suggest that the layerings are a global feature of the comet nucleus that provide information about formation and evolution of comet 67P. The furrows are non-uniformly distributed throughout the image. Their orientation is broadly parallel to the direction of the local gravity vector at the Hathor cliff, with spacings similar to those of the layering structures. The furrows are interpreted as signatures of local down-slope movement of cliff material. We demonstrate that the developed method is broadly applicable to the detection and analysis of various kinds of quasi-periodic structures like geological layering, folding and faulting, and texture analysis in general. In order to facilitate the application of our method, this paper is accompanied by a demo program written in MATLAB.

关键词： methods: data analysis techniques: image processing comets: general comets: individual: 67P/Churyumov Gerasimenko

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image Inpainting using Automatic Structure Propagation with Auxiliary Line Construction

Image Inpainting using Automatic Structure Propagation with ...

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Summer Virtual Conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed Computing (SNPD-Summer), ACIS International

作者： Yuto Urano Irawati Nurmala Sari Weiwei Du Department of Information Science Kyoto Institute of Technology Kyoto Japan Information and Human Science Kyoto Institute of Technology Kyoto Japan

ISBN: (纸本)9798350396386

Existing image inpainting methods used traditional and deep learning methods to restore a large missing region in the damaged image. This often leads to color discrepancy and blurriness. Pre-processing of prior line detection by user assistance is usually employed to reduce the blurry of center region by segmenting the large region into more minor. However, it operates manually, which is time-consuming. This paper introduces a technique to generate two-line types: penetrator and interactor in constructing auxiliary lines as guidance. These lines assist structure propagation established automatically, while the remaining small regions are filled by texture propagation. Experiments on large regular masks demonstrate that our proposed approach generates higher-quality results than other methods.

关键词： Deep learning image segmentation image color analysis image restoration Artificial intelligence Software engineering

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Instant water body variation detection via analysis on remote sensing imagery

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JOURNAL OF REAL-TIME image processing 2021年第5期18卷 1577-1590页

作者： Wu, Yirui Han, Pengfei Zheng, Zhan Hohai Univ Coll Comp & Informat Nanjing Peoples R China

Water resource is one of the most valuable natural resources for human beings, which requires to be monitored for careful protection. Inspired by a significant power of machine learning methods, researchers have successfully developed many applications to automatically perform identification on the water body via analyzing remote sensing images. Since a similar category of ground objects could show a large difference in spectral representation, researchers try to propose distinctive and effective features to offer redundant information for category classification. Moreover, large amount of high-resolution remote sensing images require analyzing algorithms to be parallel processed for instant feedback. Based on these requirements, we propose a novel water body variation detection via analysis on remote sensing images. Specifically, the proposed method firstly perform pixel-level classification to locate abnormal changes with thoughts of visual word patterns. Afterwards, the proposed method proposes block division method to construct parallel running version with Mapreduce structure. With high representational and parallel running abilities, the proposed method is capable to accurately detect variation areas on remote sensing images with instant feedback. Experiments on several self-collected datasets show the proposed method has achieved better efficiencies than comparative studies.

关键词： Real-time RS applications of detection and estimation theory Remote sensing images Water body variation detection method distributed processing

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Cuckoo Search Optimized Histogram Equalization for Low Contrast image Enhancement

Cuckoo Search Optimized Histogram Equalization for Low Contr...

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International Conference on parallel distributed and Grid Computing (PDGC)

作者： Niveditta Thakur Nafis Uddin Khan Sunil Datt Sharma Jaypee University of Information Technology Solan India

ISBN: (纸本)9781665454025

image enhancement is a process to improve the visual standard of image so as to extract spatial features of image. Histogram Equalization is method by which image can be improved for better perception and interpretation by different automated image processing system and human beings. Although, for low-contrast images (with lower dynamic range) traditional histogram equalization deteriorate quality of the output image by introducing washed-out form caused by too much brightness change. This paper presents histogram equalization based image enhancement method which is optimized using cuckoo search algorithm. Foremost purpose of the proposed method is to control over and under enhancement by calculating clip limits of the image histogram before performing histogram equalization. This method uses cuckoo search algorithm to automatically control the clip limit according to the image nature using improved fitness function. Effectiveness of the proposed method in comparison to other methods is analyzed using well known image quality metrics.

关键词： image quality Histograms Visualization Heuristic algorithms Feature extraction Noise measurement Indexes

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distributed algorithms for scalable proximity operator computation and application to video denoising

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DIGITAL SIGNAL processing 2022年第0期128卷

作者： Abboud, Feriel Stamm, Marin Chouzenoux, Emilie Pesquet, Jean-Christophe Talbot, Hugues WITBE Collines Arche Immeuble Opera F-92800 Puteaux La Defense France Inst Polytech Paris ENSTA Paris Palaiseau France Univ Paris Saclay Ctr Visual Comp Cent Supelec Inria Gif Sur Yvette France

Optimization problems arising in signal and image processing involve an increasingly large number of variables. In addition to the curse of dimensionality, another difficulty to overcome is that the cost function usually reads as the sum of several loss or regularization terms, which are non-necessarily smooth and possibly composed with large-size linear operators. Proximal splitting approaches are fundamental tools to address such problems, with demonstrated efficiency in many applicative fields. In this paper, we present a new distributed algorithm for computing the proximity operator of a sum of non-necessarily smooth convex functions composed with arbitrary linear operators. Our algorithm relies on a primal-dual splitting strategy, and benefits from established convergence guaranties. Each involved function is associated with a node of a hypergraph, with the ability to communicate with neighboring nodes sharing the same hyperedge. Thanks to this structure, our method can be efficiently implemented on modern parallel computing architectures, distributing the computations on multiple nodes or machines, with controlled requirements for synchronization steps. Good numerical performance and scalability properties are demonstrated on a problem of video sequence denoising. Our code implemented in Julia is made available at https://github .com /MarinENSTA /distributed_julia_denoising. (C) 2022 Elsevier Inc. All rights reserved.

关键词： Convex optimization Proximal methods distributed algorithm parallel programming Video restoration

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A Strategy of parallel SLIC Superpixels for Handling Large-Scale images over Apache Spark

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REMOTE SENSING 2022年第7期14卷 1568-1568页

作者： Wang, Ning Chen, Fang Yu, Bo Wang, Lei Chinese Acad Sci Aerosp Informat Res Inst Key Lab Digital Earth Sci 9 Dengzhuang South Rd Beijing 100094 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Chinese Acad Sci Aerosp Informat Res Inst State Key Lab Remote Sensing Sci Beijing 100101 Peoples R China Chinese Acad Sci Aerosp Informat Res Inst Hainan Key Lab Earth Observat Sanya 572029 Peoples R China

Superpixel segmentation algorithms are widely used in the image processing field. The size of the large-scale images usually exceeds the memory of a single machine given that the size of image data has increased rapidly in recent years. This leads to big challenges for implementing sequential superpixel segmentation methods, although these algorithms have good scalability. Additionally, segmentation of large-scale images over a distributed cluster is a feasible solution. Nevertheless, it is challenging to transplant sequential superpixel algorithms directly to a distributed environment, as usually there are incomplete object problems in the border area of image tiles. To overcome the incomplete object problems, one approach is to build a distributed strategy based on a sequential SLIC superpixel segmentation algorithm over a distributed cluster organized by Apache Spark. In our research, the decomposed image tiles were divided into two categories-even tiles and odd tiles. The even tiles were first segmented by the SLIC algorithm, then the cluster centers and buffer sizes of even tiles were extracted and switched to odd tiles. During the shuffle stage, the odd tiles acquired pixels from adjacent even tiles according to the buffer sizes, and then the buffered odd tiles were segmented by the SLIC algorithm with the help of the shared cluster centers. The superpixels with shared cluster centers were generated in even tiles and remained in order to enlarge the odd tiles rather than redundant computing of specific areas to modify incomplete superpixels well. Specifically, this strategy employs the shared variables to transmit intermediate results and the shuffle operations were carried out among approximately half of the entire image tiles, which reduces the communications further. The distributed strategy was evaluated in terms of the accuracy and execution efficiency, which revealed that the proposed strategy could not only get better F-measure values but is also implem

关键词： superpixel algorithms distributed computation image processing Apache Spark digital disaster reduction

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Edge-enhanced GAN with Vanishing Points for image Inpainting

Edge-enhanced GAN with Vanishing Points for Image Inpainting

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Summer Virtual Conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed Computing (SNPD-Summer), ACIS International

作者： Kei Masaoka Irawati Nurmala Sari Weiwei Du Department of Information Science Kyoto Institute of Technology Kyoto Japan Information and Human Science Kyoto Institute of Technology Kyoto Japan

ISBN: (纸本)9798350396386

Reconstructing the damaged images with perspective views has an extensive range in the field of image inpainting. However, most existing methods generated inadequately realistic restored images. Accomplishing this problem, we propose an edge-enhanced image generation model considering viewpoints. Our method applies edge map information to guide image generation based on the perspective views of an image using vanishing points detection. Texture synthesis will be presented as post-processing to complete the remaining missing regions. Experiment shows that our approach can generate perspective images with convincing details, such as indoor and outdoor facades.

关键词： image synthesis image edge detection Generative adversarial networks image restoration Artificial intelligence image reconstruction Software engineering

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distributed Acoustic Sensing for Vehicle Speed and Traffic Flow Estimation

Distributed Acoustic Sensing for Vehicle Speed and Traffic F...

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IEEE Intelligent Transportation Systems Conference (ITSC)

作者： Wiesmeyr, Christoph Coronel, Carmina Litzenberger, Martin Doeller, Herbert Josef Schweiger, Hans-Bernhard Calbris, Gaetan AIT Austrian Inst Technol GmbH Vienna Austria Dr Doller Vermessung ZT GmbH Vienna Austria Febus Opt Pau France

ISBN: (纸本)9781728191423

For traffic monitoring systems it is desirable to have a low-cost, low-maintenance, and reliable system to facilitate continuous and safe traffic flow. In line with this, we introduce distributed acoustic sensing (DAS) for traffic monitoring applications. In DAS systems, series of light pulses are transmitted along a fiber-optic cable and the back-scattered light, which is affected by the mechanical strain of the fiber-optic cables due to ground vibrations, is measured and analyzed. With fiber-optic cables installed parallel to a highway where ground vibrations are induced by passing vehicles, traffic information such as vehicle flow and average speeds can be estimated from the DAS signals. In this paper, we present an algorithm based on image processing methods that estimates traffic information from image representations generated from 1-minute segments of DAS signals. We tested the results of the algorithm on DAS data recording on a real highway against reference traffic data measured by road-side sensors.

关键词： Vibrations Optical fiber sensors Roads Optical fiber cables Estimation Mechanical cables image representation

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