Shengchun Wang¹, Peiqi Chen¹, Jingui Huang^1,*, Tsz Ho Wong²

Computer Systems Science and Engineering, Vol.40, No.3, pp. 1167-1181, 2022, DOI:10.32604/csse.2022.018911 - 24 September 2021

Abstract We propose an end-to-end dehazing model based on deep learning (CNN network) and uses the dehazing model re-proposed by AOD-Net based on the atmospheric scattering model for dehazing. Compare to the previously proposed dehazing network, the dehazing model proposed in this paper make use of the FPN network structure in the field of target detection, and uses five feature maps of different sizes to better obtain features of different proportions and different sub-regions. A large amount of experimental data proves that the dehazing model proposed in this paper is superior to previous dehazing technologies in… More >

Samia Riaz¹, Muhammad Waqas Anwar², Irfan Riaz³, Hyun-Woo Kim⁴, Yunyoung Nam^4,*, Muhammad Attique Khan⁵

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1-17, 2022, DOI:10.32604/cmc.2022.018268 - 07 September 2021

Abstract The captured outdoor images and videos may appear blurred due to haze, fog, and bad weather conditions. Water droplets or dust particles in the atmosphere cause the light to scatter, resulting in very limited scene discernibility and deterioration in the quality of the image captured. Currently, image dehazing has gained much popularity because of its usability in a wide variety of applications. Various algorithms have been proposed to solve this ill-posed problem. These algorithms provide quite promising results in some cases, but they include undesirable artifacts and noise in haze patches in adverse cases. Some… More >

Mahmood ul Hassan^1,*, Amin Al-Awady¹, Khalid Mahmood², Shahzad Ali³, Ibrahim Algamdi¹, Muhammad Kashif Saeed⁴, Safdar Zaman⁵

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3413-3427, 2021, DOI:10.32604/cmc.2021.018544 - 24 August 2021

Abstract Wireless Sensor Networks (WSNs) are an integral part of the Internet of Things (IoT) and are widely used in a plethora of applications. Typically, sensor networks operate in harsh environments where human intervention is often restricted, which makes battery replacement for sensor nodes impractical. Node failure due to battery drainage or harsh environmental conditions poses serious challenges to the connectivity of the network. Without a connectivity restoration mechanism, node failures ultimately lead to a network partition, which affects the basic function of the sensor network. Therefore, the research community actively concentrates on addressing and solving… More >

Mahmood ul Hassan^1,*, 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 >

Chung-Il Kim¹, Jehyeok Rew², Yongjang Cho², Eenjun Hwang^2,*

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 >

Ghulfam Zahra¹, Muhammad Imran¹, Abdulrahman M. Qahtani^2,*, 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 >

Yuye Zhang^1,*, 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 >

Mushtaq Ahmad Khan^1,*, Ahmed B. Altamimi², Zawar Hussain Khan³, Khurram Shehzad Khattak³, Sahib Khan^4,*, 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 >

Yao-Liang Chung^1,*, 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 >

Leilei Geng¹, Chaoran Cui¹, Qiang Guo¹, Sijie Niu², Guoqing Zhang³, Peng Fu^{4, *}

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 >