压缩编码孔径红外成像超分辨重建

doi:10.13229/j.cnki.jdxbgxb201604033

吉林大学学报(工学版) ›› 2016, Vol. 46 ›› Issue (4): 1239-1245.doi: 10.13229/j.cnki.jdxbgxb201604033

压缩编码孔径红外成像超分辨重建

王新华^{1, 2}, 欧阳继红¹, 庞武斌²

1.吉林大学计算机科学与技术学院,长春 130012;
2.中国科学院长春光学精密机械与物理研究所应用光学国家重点实验室,长春 130033

收稿日期:2015-03-05 出版日期:2016-07-20 发布日期:2016-07-20
通讯作者: 欧阳继红(1964-),女,教授,博士生导师.研究方向:空间推理与数据挖掘.E-mail:ouyj@jlu.edu.cn
作者简介:王新华(1984-),男,工程师,博士研究生.研究方向:计算光学与机器视觉.E-mail:xinhuajlu@163.com
基金资助:
国家自然科学基金项目(61170092,61133011)

Supper-resolution reconstruction of infrared images of compressive coded aperture

WANG Xin-hua^{1, 2}, OUYANG Ji-hong¹, PANG Wu-bin²

1.College of Computer Science and Technology, Jilin University, Changchun 130012, China;
2. State Key Laboratory of Applied Optics,Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China

Received:2015-03-05 Online:2016-07-20 Published:2016-07-20

摘要/Abstract

摘要： 为了利用低分辨率红外探测器获取高质量图像信息,对基于频谱面的压缩编码孔径成像方法和超分辨率图像重建算法进行了研究。首先,在频谱面加入孔径编码器,通过傅里叶变换对采样图像信号进行编码压缩。然后,利用光学成像系统的分片光滑性,实现信号在傅里叶变换域的稀疏表示。最后,提出了两点步长梯度法与自适应非单调线搜索策略相结合的梯度投影并行加速算法,用于完成对稀疏信号的超分辨重建。实验结果表明,该算法能够以远小于原始信号的数据量重建出高分辨率图像信息。

关键词: 计算机应用, 压缩感知, 编码孔径, 超分辨重建

Abstract: In order to obtain high quality image information using infrared detector with low resolution, a compressive coded aperture imaging method based on the frequency spectrum plane and the Supper Resolution Image Reconstruction (SRIR) algorithm was investigated. First, the aperture encoder was added to the frequency spectrum plane, and the image sampling signal was compressive coded by Fourier transform. The, by virtue of the piecewise smooth of the optimal imaging system, the signal sparse representation was realized based on Fourier transform domain. Finally, the SRIR of the sparse signal was completed by improved Gradient Projection for Sparse Reconstruction (GPSR) parallel acceleration algorithm, which combined with GPSR-BB algorithm and adaptive non-monotone line search strategy. Experimental results indicate that the high resolution images can be constructed with information far less than that of the original signal.

Key words: computer application, compressed sensing, coded aperture, super resolution image reconstruction (SRIR)

中图分类号:

TP394.1

王新华, 欧阳继红, 庞武斌. 压缩编码孔径红外成像超分辨重建[J]. 吉林大学学报(工学版), 2016, 46(4): 1239-1245.

WANG Xin-hua, OUYANG Ji-hong, PANG Wu-bin. Supper-resolution reconstruction of infrared images of compressive coded aperture[J]. 吉林大学学报(工学版), 2016, 46(4): 1239-1245.

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压缩编码孔径红外成像超分辨重建

Supper-resolution reconstruction of infrared images of compressive coded aperture

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