| 一种基于单像素相机的压缩感知图像重建优化算法 |
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| 引用本文： | 魏子然,张建林,徐智勇,刘永.一种基于单像素相机的压缩感知图像重建优化算法[J].半导体光电,2019,40(3):449-454. |
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| 作者姓名： | 魏子然 张建林 徐智勇 刘永 |
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| 作者单位： | 中国科学院光电技术研究所, 成都 610209;电子科技大学 光电科学与工程学院, 成都 610054;中国科学院光束控制重点实验室, 成都 610209;中国科学院大学, 北京 100049,中国科学院光电技术研究所, 成都 610209;中国科学院光束控制重点实验室, 成都 610209,中国科学院光电技术研究所, 成都 610209;中国科学院光束控制重点实验室, 成都 610209,电子科技大学 光电科学与工程学院, 成都 610054 |
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| 摘 要： | 基于压缩感知图像重构和单像素相机成像的基本原理,对单像素成像系统中的图像重建算法进行了改进优化。基于最小范数类优化算法,结合凸优化算法和非凸优化算法各自的优点,设计了一种逼近L0范数的数学模型,从而实现了从凸优化向非凸优化算法的迭代逼近,即逼近光滑L0范数算法。该新型算法以更高的效率和更大的概率逼近原始信号全局最优且尽可能稀疏的解。相较于传统压缩感知图像重建的贪婪类算法和最小范数类算法,该算法使压缩感知重建图像的质量和单像素相机的成像效果均得到了有效提升,并通过实验仿真和实际场景的成像实验验证了该优化算法的可行性。
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| 关 键 词： | 单像素相机 压缩感知 稀疏信号 全局最优 图像重构 |
| 收稿时间： | 2019/1/7 0:00:00 |
An Optimization Algorithm for Compressed Sensing Image Reconstruction Based on Single Pixel Camera |
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| WEI Ziran,ZHANG Jianlin,XU Zhiyong and LIU Yong.An Optimization Algorithm for Compressed Sensing Image Reconstruction Based on Single Pixel Camera[J].Semiconductor Optoelectronics,2019,40(3):449-454. |
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| Authors: | WEI Ziran ZHANG Jianlin XU Zhiyong and LIU Yong |
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| Affiliation: | Institute of Optics and Electronics of The Chinese Academy of Sciences, Chengdu 610209, CHN;School of Optoelectronic Science and Engin., University of Electronic Science and Technology of China, Chengdu 610054, CHN;Key Lab.of Optical Engin.of The Chinese Academy of Sciences, Chengdu 610209, CHN;University of Chinese Academy of Sciences, Beijing 100049, CHN,Institute of Optics and Electronics of The Chinese Academy of Sciences, Chengdu 610209, CHN;Key Lab.of Optical Engin.of The Chinese Academy of Sciences, Chengdu 610209, CHN,Institute of Optics and Electronics of The Chinese Academy of Sciences, Chengdu 610209, CHN;Key Lab.of Optical Engin.of The Chinese Academy of Sciences, Chengdu 610209, CHN and School of Optoelectronic Science and Engin., University of Electronic Science and Technology of China, Chengdu 610054, CHN |
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| Abstract: | Based on the basic principles of single-pixel camera imaging and compressed sensing image reconstruction, the image reconstruction algorithm of single-pixel camera was optimized. Based on the optimization algorithm of minimum norm and by combining the advantages of convex optimization and non-convex optimization, a mathematical model approximating L0 norm was designed to realize the iterative approximation from convex optimization to non-convex optimization, and a new algorithm approximating the smooth L0 norm algorithm was proposed. The proposed algorithm approximates the global optimal solution as sparse as possible with higher efficiency and greater probability. Compared with the traditional greedy algorithm and minimum norm algorithm, the new algorithm improves the quality of reconstructed images and imaging effectively, and its feasibility was verified by simulations and actual single-pixel imaging experiments. |
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| Keywords: | single-pixel camera compressed sensing sparse signal global optimum image reconstruction |
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