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  • Open Access

    ARTICLE

    An Efficient Connectivity Restoration Technique (ECRT) for Wireless Sensor Network

    Mahmood ul Hassan1,*, Shahzad Ali2, Khalid Mahmood3, Muhammad Kashif Saeed4, Amin Al-Awady1, Kamran Javed5, Ansar Munir Shah6

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1003-1019, 2021, DOI:10.32604/cmc.2021.018264 - 04 June 2021

    Abstract Node failure in Wireless Sensor Networks (WSNs) is a fundamental problem because WSNs operate in hostile environments. The failure of nodes leads to network partitioning that may compromise the basic operation of the sensor network. To deal with such situations, a rapid recovery mechanism is required for restoring inter-node connectivity. Due to the immense importance and need for a recovery mechanism, several different approaches are proposed in the literature. However, the proposed approaches have shortcomings because they do not focus on energy-efficient operation and coverage-aware mechanisms while performing connectivity restoration. Moreover, most of these approaches… More >

  • Open Access

    ARTICLE

    UFC-Net with Fully-Connected Layers and Hadamard Identity Skip Connection for Image Inpainting

    Chung-Il Kim1, Jehyeok Rew2, Yongjang Cho2, Eenjun Hwang2,*

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3447-3463, 2021, DOI:10.32604/cmc.2021.017633 - 06 May 2021

    Abstract Image inpainting is an interesting technique in computer vision and artificial intelligence for plausibly filling in blank areas of an image by referring to their surrounding areas. Although its performance has been improved significantly using diverse convolutional neural network (CNN)-based models, these models have difficulty filling in some erased areas due to the kernel size of the CNN. If the kernel size is too narrow for the blank area, the models cannot consider the entire surrounding area, only partial areas or none at all. This issue leads to typical problems of inpainting, such as pixel More >

  • Open Access

    ARTICLE

    Visibility Enhancement of Scene Images Degraded by Foggy Weather Condition: An Application to Video Surveillance

    Ghulfam Zahra1, Muhammad Imran1, Abdulrahman M. Qahtani2,*, Abdulmajeed Alsufyani2, Omar Almutiry3, Awais Mahmood3, Fayez Eid Alazemi4

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3465-3481, 2021, DOI:10.32604/cmc.2021.017454 - 06 May 2021

    Abstract In recent years, video surveillance application played a significant role in our daily lives. Images taken during foggy and haze weather conditions for video surveillance application lose their authenticity and hence reduces the visibility. The reason behind visibility enhancement of foggy and haze images is to help numerous computer and machine vision applications such as satellite imagery, object detection, target killing, and surveillance. To remove fog and enhance visibility, a number of visibility enhancement algorithms and methods have been proposed in the past. However, these techniques suffer from several limitations that place strong obstacles to… More >

  • Open Access

    ARTICLE

    Motion-Blurred Image Restoration Based on Joint Invertibility of PSFs

    Yuye Zhang1,*, Jingli Huang1, Jiandong Liu1, Hakeel Ahmed Chohan2

    Computer Systems Science and Engineering, Vol.36, No.2, pp. 407-416, 2021, DOI:10.32604/csse.2021.014154 - 05 January 2021

    Abstract To implement restoration in a single motion blurred image, the PSF (Point Spread Function) is difficult to estimate and the image deconvolution is ill-posed as a result that a good recovery effect cannot be obtained. Considering that several different PSFs can get joint invertibility to make restoration well-posed, we proposed a motion-blurred image restoration method based on joint invertibility of PSFs by means of computational photography. Firstly, we designed a set of observation device which composed by multiple cameras with the same parameters to shoot the moving target in the same field of view continuously… More >

  • Open Access

    ARTICLE

    Multiquadric Radial Basis Function Approximation Scheme for Solution of Total Variation Based Multiplicative Noise Removal Model

    Mushtaq Ahmad Khan1,*, Ahmed B. Altamimi2, Zawar Hussain Khan3, Khurram Shehzad Khattak3, Sahib Khan4,*, Asmat Ullah3, Murtaza Ali1

    CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.1, pp. 55-88, 2021, DOI:10.32604/cmes.2021.011163 - 22 December 2020

    Abstract This article introduces a fast meshless algorithm for the numerical solution nonlinear partial differential equations (PDE) by Radial Basis Functions (RBFs) approximation connected with the Total Variation (TV)-based minimization functional and to show its application to image denoising containing multiplicative noise. These capabilities used within the proposed algorithm have not only the quality of image denoising, edge preservation but also the property of minimization of staircase effect which results in blocky effects in the images. It is worth mentioning that the recommended method can be easily employed for nonlinear problems due to the lack of More >

  • Open Access

    ARTICLE

    A Study of Single Image Haze Removal Using a Novel White-Patch RetinexBased Improved Dark Channel Prior Algorithm

    Yao-Liang Chung1,*, Hung-Yuan Chung2, Yu-Shan Chen2

    Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 367-383, 2020, DOI:10.31209/2020.100000206

    Abstract In this study, we introduce an algorithm which is based on a series of wellknown algorithms and mainly uses an improved dark channel prior algorithm and the White-Patch Retinex algorithm (both are heterogeneous algorithms) in order to effectively remove the haze from a single image. When used in conjunction with a heterogeneous architecture, the value of the algorithm becomes even greater. With an effective design and a novel procedure, the proposed algorithm can not only restore a clear image, but also solve the halo effect, color distortion, and long operating time issues resulting from the More >

  • Open Access

    ARTICLE

    Robust Core Tensor Dictionary Learning with Modified Gaussian Mixture Model for Multispectral Image Restoration

    Leilei Geng1, Chaoran Cui1, Qiang Guo1, Sijie Niu2, Guoqing Zhang3, Peng Fu4, *

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 913-928, 2020, DOI:10.32604/cmc.2020.09975 - 23 July 2020

    Abstract The multispectral remote sensing image (MS-RSI) is degraded existing multispectral camera due to various hardware limitations. In this paper, we propose a novel core tensor dictionary learning approach with the robust modified Gaussian mixture model for MS-RSI restoration. First, the multispectral patch is modeled by three-order tensor and high-order singular value decomposition is applied to the tensor. Then the task of MS-RSI restoration is formulated as a minimum sparse core tensor estimation problem. To improve the accuracy of core tensor coding, the core tensor estimation based on the robust modified Gaussian mixture model is introduced More >

  • Open Access

    ARTICLE

    The Optimization Study about Fault Self-Healing Restoration of Power Distribution Network Based on Multi-Agent Technology

    Fuquan Huang1, Zijun Liu1, Tinghuang Wang1, Haitai Zhang2, *, Tony Yip3

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 865-878, 2020, DOI:10.32604/cmc.2020.010724 - 23 July 2020

    Abstract In order to quickly and accurately locate the fault location of the distribution network and increase the stability of the distribution network, a fault recovery method based on multi-objective optimization algorithm is proposed. The optimization of the power distribution network fault system based on multiagent technology realizes fast recovery of multi-objective fault, solve the problem of network learning and parameter adjustment in the later stage of particle swarm optimization algorithm falling into the local extreme value dilemma, and realize the multi-dimensional nonlinear optimization of the main grid and the auxiliary grid. The system proposed More >

  • Open Access

    ARTICLE

    A Fast Filling Algorithm for Image Restoration Based on Contour Parity

    Yan Liu1, *, Wenxin Hu1, *, Longzhe Han2, Maksymyuk Taras3, Zhiyun Chen1

    CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 509-519, 2020, DOI:10.32604/cmc.2020.07519 - 30 March 2020

    Abstract Filling techniques are often used in the restoration of images. Yet the existing filling technique approaches either have high computational costs or present problems such as filling holes redundantly. This paper proposes a novel algorithm for filling holes and regions of the images. The proposed algorithm combines the advantages of both the parity-check filling approach and the region-growing inpainting technique. Pairing points of the region’s boundary are used to search and to fill the region. The scanning range of the filling method is within the target regions. The proposed method does not require additional working More >

  • Open Access

    ARTICLE

    Overview of Digital Image Restoration

    Wei Chen1, 2, Tingzhu Sun1, 2, Fangming Bi1, 2, *, Tongfeng Sun1, 2, Chaogang Tang1, 2, Biruk Assefa1, 3

    Journal of New Media, Vol.1, No.1, pp. 35-44, 2019, DOI:10.32604/jnm.2019.05803

    Abstract Image restoration is an image processing technology with great practical value in the field of computer vision. It is a computer technology that estimates the image information of the damaged area according to the residual image information of the damaged image and carries out automatic repair. This article firstly classify and summarize image restoration algorithms, and describe recent advances in the research respectively from three aspects including image restoration based on partial differential equation, based on the texture of image restoration and based on deep learning, then make the brief analysis of digital image restoration More >

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