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

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 the real world outdoor computer… 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

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 to obtain the target images… 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 dark channel prior. Rich experimental… 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

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 into the proposed model by… More >

Yan Liu^{1, *}, Wenxin Hu^{1, *}, Longzhe Han², Maksymyuk Taras³, Zhiyun Chen¹

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

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 memory or assistant colors, and… More >

Wei Chen^{1, 2}, Tingzhu Sun^{1, 2}, Fangming Bi^{1, 2, *}, Tongfeng Sun^{1, 2}, Chaogang Tang^{1, 2}, Biruk Assefa^{1, 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 of subjective and objective evaluation… More >

Zhengwei Li^1,2, Jianli Wang^1,*, Tao Chen¹, Bin Wang¹, Yuanhao Wu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.117, No.2, pp. 271-286, 2018, DOI:10.31614/cmc.2018.04005

Abstract With the development of adaptive optics and post restore processing techniques, large aperture ground-based telescopes can obtain high-resolution images (HRIs) of targets. The pose of the space target can be estimated from HRIs by several methods. As the target features obtained from the image are unstable, it is difficult to use existing methods for pose estimation. In this paper a method based on real-time target model matching to estimate the pose of space targets is proposed. First, the physically-constrained iterative deconvolution algorithm is used to obtain HRIs of the space target. Second, according to the 3D model, the ephemeris data,… More >