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  • Open Access

    ARTICLE

    Image Reconstruction for ECT under Compressed Sensing Framework Based on an Overcomplete Dictionary

    Xuebin Qin1,*, Yutong Shen1, Jiachen Hu1, Mingqiao Li1, Peijiao Yang1, Chenchen Ji1, Xinlong Zhu2

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1699-1717, 2022, DOI:10.32604/cmes.2022.018234 - 30 December 2021

    Abstract Electrical capacitance tomography (ECT) has great application potential in multiphase process monitoring, and its visualization results are of great significance for studying the changes in two-phase flow in closed environments. In this paper, compressed sensing (CS) theory based on dictionary learning is introduced to the inverse problem of ECT, and the K-SVD algorithm is used to learn the overcomplete dictionary to establish a nonlinear mapping between observed capacitance and sparse space. Because the trained overcomplete dictionary has the property to match few features of interest in the reconstructed image of ECT, it is not necessary More >

  • Open Access

    ARTICLE

    STRASS Dehazing: Spatio-Temporal Retinex-Inspired Dehazing by an Averaging of Stochastic Samples

    Zhe Yu1, Bangyong Sun1,3,*, Di Liu2, Vincent Whannou de Dravo1, Margarita Khokhlova4, Siyuan Wu3

    Journal of Renewable Materials, Vol.10, No.5, pp. 1381-1395, 2022, DOI:10.32604/jrm.2022.018262 - 22 December 2021

    Abstract In this paper, we propose a neoteric and high-efficiency single image dehazing algorithm via contrast enhancement which is called STRASS (Spatio-Temporal Retinex-Inspired by an Averaging of Stochastic Samples) dehazing, it is realized by constructing an efficient high-pass filter to process haze images and taking the influence of human vision system into account in image dehazing principles. The novel high-pass filter works by getting each pixel using RSR and computes the average of the samples. Then the low-pass filter resulting from the minimum envelope in STRESS framework has been replaced by the average of the samples. More >

  • Open Access

    ARTICLE

    Damage Detection for CFRP Based on Planar Electrical Capacitance Tomography

    Wenru Fan, Chi Wang*

    Structural Durability & Health Monitoring, Vol.14, No.4, pp. 303-314, 2020, DOI:10.32604/sdhm.2020.011009 - 04 December 2020

    Abstract Due to the widespread use of carbon fiber reinforced polymer/plastic (CFRP), the nondestructive structural health monitoring for CFRP is playing an increasingly essential role. As a nonradiative, noninvasive and nondestructive detection technique, planar electrical capacitance tomography (PECT) electrodes array is employed in this paper to reconstruct the damage image according to the calculated dielectric constant changes. The shape and duty ratio of PECT electrodes are optimized according to the relations between sensitivity distribution and the dielectric constant of different anisotropic degrees. The sensitivity matrix of optimized PECT sensor is more uniform as the result shows, More >

  • Open Access

    ARTICLE

    Image Reconstruction Based on Compressed Sensing Measurement Matrix Optimization Method

    Caifeng Cheng1,2, Deshu Lin3,*

    Journal on Internet of Things, Vol.2, No.1, pp. 47-54, 2020, DOI:10.32604/jiot.2020.09117 - 06 August 2020

    Abstract In this paper, the observation matrix and reconstruction algorithm of compressed sensing sampling theorem are studied. The advantages and disadvantages of greedy reconstruction algorithm are analyzed. The disadvantages of signal sparsely are preset in this algorithm. The sparsely adaptive estimation algorithm is proposed. The compressed sampling matching tracking algorithm supports the set selection and culling atomic standards to improve. The sparse step size adaptive compressed sampling matching tracking algorithm is proposed. The improved algorithm selects the sparsely as the step size to select the support set atom, and the maximum correlation value. Half of the More >

  • Open Access

    ABSTRACT

    Image reconstruction using the fictitious time integration method (FTIM)

    I-Yao CHAN, Chein-Shan Liu, Weichung Yeih

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.20, No.2, pp. 53-54, 2011, DOI:10.3970/icces.2011.020.053

    Abstract In this study, we adopt the fictitious time integration method to treat the image reconstruction problem. The distorted image is considered as a result of diffused data from the initial perfect image by using a nonlinear diffusion equation. The image reconstruction problem then becomes an inverse problem by using the data in the final time to recover the data in the initial time. This inverse problem is known as the backward in time nonlinear diffusion problem which is highly ill-posed. We propose to use the fictitious time integration method to tackle this highly ill-posed image More >

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