摘要：
Purpose - The purpose of this paper is to develop a compressive sensing (CS) algorithm for noisy solder joint imagery compression and recovery. A fast gradient-based compressive sensing (FGbCS) approach is proposed based on the convex optimization. The proposed algorithm is able to improve performance in terms of peak signal noise ratio (PSNR) and computational cost. Design/methodology/approach - Unlike traditional CS methods, the authors first transformed a noise solder joint image to a sparse signal by a discrete cosine transform (DCT), so that the reconstruction of noisy solder joint imagery is changed to a convex optimization problem. Then, a so-called gradient-based method is utilized for solving the problem. To improve the method efficiency, the authors assume the problem to be convex with the Lipschitz gradient through the replacement of an iteration parameter by the Lipschitz constant. Moreover, a FGbCS algorithm is proposed to recover the noisy solder joint imagery under different parameters. Findings - Experiments reveal that the proposed algorithm can achieve better results on PNSR with fewer computational costs than classical algorithms like Orthogonal Matching Pursuit (OMP), Greedy Basis Pursuit (GBP), Subspace Pursuit (SP), Compressive Sampling Matching Pursuit (CoSaMP) and Iterative Re-weighted Least Squares (IRLS). Convergence of the proposed algorithm is with a faster rate O(kk) instead of O(1/k). Practical implications - This paper provides a novel methodology for the CS of noisy solder joint imagery, and the proposed algorithm can also be used in other imagery compression and recovery. Originality/value - According to the CS theory, a sparse or compressible signal can be represented by a fewer number of bases than those required by the Nyquist theorem. The new development might provide some fundamental guidelines for noisy imagery compression and recovering.
期刊：
IET Communications,2015年9(7):940-946 ISSN：1751-8628
通讯作者：
Zhao, Huihuang
作者机构：
[Zhao, Huihuang; Peng, Xiaojiang] Hengyang Normal Univ, Dept Comp Sci, Hengyang, Hunan, Peoples R China.;[Zhao, Huihuang; Wang, Yaonan] Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Hunan, Peoples R China.;[Qiao, Zhijun] Univ Texas Pan Amer, Dept Math, Edinburg, TX 78539 USA.
通讯机构：
[Zhao, Huihuang] H;Hengyang Normal Univ, Dept Comp Sci, Hengyang, Hunan, Peoples R China.
关键词：
image reconstruction;video signal processing;compressed sensing;convex programming;minimisation;noise image reconstruction;noise video reconstruction;fast gradient-based compressive sensing;orthogonal transformation;convex optimisation problem;gradient-based method;signal reconstruction;convex minimisation problem;convex optimisation;noise signal reconstruction;Lipschitz gradient;iteration parameter;FGB-CS method
摘要：
In this study, a fast gradient-based compressive sensing (FGB-CS) for noise image and video is proposed. Given a noise image or video, the authors first make it sparse by orthogonal transformation, and then reconstruct it by solving a convex optimisation problem with a novel gradient-based method. The main contribution is twofold. Firstly, they deal with the noise signal reconstruction as a convex minimisation problem, and propose a new compressive sensing based on gradient-based method for noise image and video. Secondly, to improve the computational efficiency of gradient-based compressive sensing, they formulate the convex optimisation of noise signal reconstruction under Lipschitz gradient and replace the iteration parameter by the Lipschitz constant. With this strategy, the convergence of our FGB-CS is reduced from O(1/k) to O(1/k2). Experimental results indicate that their FGB-CS method is able to achieve better performance than several classical algorithms.
期刊：
Solar Energy,2011年85(10):2551-2559 ISSN：0038-092X
通讯作者：
Yang, Wenji
作者机构：
[Wang, Yanguo; Yu, Hongchun; Yang, Wenji] Hunan Univ, Coll Phys & Microelect Sci, Micronano Technol Res Ctr, Changsha 410082, Hunan, Peoples R China.;[Wan, Qing; Tang, Jianping; Su, Yingbing] Hunan Univ, Minist Educ, Key Lab Micronano Optoelect Devices, Changsha 410082, Hunan, Peoples R China.;[Tang, Jianping] Hengyang Normal Univ, Dept Phys & Elect Sci, Hengyang 422008, Peoples R China.
通讯机构：
[Yang, Wenji] H;Hunan Univ, Coll Phys & Microelect Sci, Micronano Technol Res Ctr, Changsha 410082, Hunan, Peoples R China.
关键词：
Thin film silicon solar cell;Anti-reflection;Light trapping;Omnidirectionality
摘要：
A theoretical model for an all-in-one thin film silicon solar cell (TFSSC) design with the anti-reflection (AR) coatings, the transparent electrodes, the silicon and the back reflective coatings all deposited on one piece of glass is proposed and the optical performance for the design is numerically simulated. The calculated average reflectance over the wavelength range of 0.4-1.0 mu m and incident angles from 0 degrees to 75 degrees for the optimized dual-AR coatings as a whole is 3.67% - ranking among the lowest values for current AR coatings on silicon solar cells. Furthermore, the spectrum-averaged absorptance (SAA) in the 5-mu m-thick cell in the 0.3-1.2 mu m wavelength range decreases only by 2.58% when the incident angle varies from 0 degrees to 75 degrees, clearly showing the omnidirectional characteristics of the dual-AR coatings. With reasonable assumption of the internal quantum efficiency (near unity), the 5-mu m cell produces a spectrum averaged external quantum efficiency (EQE) of 81.4% at 75 degrees angle of incidence - 6.7% larger than the experiment result of the best planar bulk cell. Under equal sunshine conditions, TFSSCs generally give higher output voltages than their bulk counterpart if equal light absorption is assumed, so the 5-mu m cell has the potential to reach the highest experimental conversion efficiency of the best planar bulk cell. By using a special mathematical technique, we are able to prove the angle-dependent absorption curves in the longer wavelength region tend to converge to a small neighborhood of the upper limit irrespective of significant differences between the transmission profiles. This indicates the AR requirement in the longer wavelength region can be significantly relaxed. (C) 2011 Elsevier Ltd. All rights reserved.
