Super-resolution Hyperspectral Compressed Sampling Imaging by Push-broom Coded Aperture

被引:0
作者
Li, Mengzhu [1 ,2 ]
Wang, Weizheng [1 ]
Qi, Junli [2 ,3 ]
Wang, Wei [1 ]
Liu, Jiying [2 ]
Tang, Wusheng [2 ]
Yi, Wenjun [2 ]
Guo, Yanfang [1 ,2 ]
Zhu, Mengjun [2 ]
Zhu, Jubo [2 ]
Li, Xiujian [2 ]
机构
[1] Changsha Univ Sci & Technol, Sch Commun Engn, Changsha 4100004, Peoples R China
[2] Natl Univ Def Technol, Coll Liberal Arts & Sci, Dept Phys, Changsha 410073, Peoples R China
[3] Army Acad Artillery & Air Def, Teaching & Res Dept Phys, Hefei 230031, Peoples R China
来源
ADVANCED OPTICAL IMAGING TECHNOLOGIES II | 2019年 / 11186卷
基金
中国国家自然科学基金;
关键词
Super-resolution; Hyperspectral imaging; Compressed sampling; Push-broom; Coded aperture; Computational imaging; ADAPTIVE REGULARIZATION; RESOLUTION; IMAGES; NORM;
D O I
10.1117/12.2537503
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Super-resolution hyperspectral imaging is a key technology for many applications, especially in the fields of remote sensing, military, agriculture, and geological exploration. Recovering a high resolution image needs enormous data, which puts forward very high requirements on image system hardware. Compressed sampling spectral imaging technology could well solve this problem and achieve high-resolution objects with low-resolution compressed data. In this paper, the method of a compressed sampling spectral imaging based on push-broom coded aperture and dispersion prism is proposed. A spectral aliasing image is formed when the object passing through the dispersive prism. According to the prism dispersion condition and the CCD pixel size, the visible spectrum can be divided into N spectral bands, and the measurement matrix of the coded aperture is respectively calibrated for the center wavelength of each spectral band. By controlling a stepper to implement the push broom of the coded aperture to change the measurement matrix, multiple spectral aliasing images can be obtained. The pixel size of the coded aperture becomes half of the CCD by a relay lens, which means the pixel of CCD is low-resolution for the coded aperture. The super-resolution hyperspectral image of the object is obtained by the improved LS reconstruction algorithm. Simulation results show that, the recovered hyperspectral image has twice resolution compared with the low-resolution CCD image, and the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) increase with the increasing compressed sampling hyperspectral images. For N=31, the average PSNR and SSIM recovered from six aliasing images is 22.019 and 0.235, respectively. The average PSNR and SSIM of the recovered 31 bands are also increasing with increasing aliasing images. While the aliasing imaging is 156, The average PSNR and SSIM exceeds 38 and 0.9. This method proves that super-resolution hyperspectral imaging can be achieved by capturing less low-resolution object images.
引用
收藏
页数:8
相关论文
共 21 条
  • [1] [Anonymous], 2017, Digital imaging for cultural heritage preservation: Analysis, restoration, and reconstruction of ancient artworks
  • [2] Parameter estimation in TV image restoration using variational distribution approximation
    Babacan, S. Derin
    Molina, Rafael
    Katsaggelos, Aggelos K.
    [J]. IEEE TRANSACTIONS ON IMAGE PROCESSING, 2008, 17 (03) : 326 - 339
  • [3] Adaptive regularization-based super resolution reconstruction technique for multi-focus low-resolution images
    Bahy, Ramy M.
    Salama, Gouda I.
    Mahmoud, Tarek A.
    [J]. SIGNAL PROCESSING, 2014, 103 : 155 - 167
  • [4] Bannore V, 2009, STUD COMPUT INTELL, V195, P1
  • [5] Bertero M., 2001, OPTICS PHOTONICS NEW, V12, P46
  • [6] Compressed sensing
    Donoho, DL
    [J]. IEEE TRANSACTIONS ON INFORMATION THEORY, 2006, 52 (04) : 1289 - 1306
  • [7] 5D MODELLING: AN EFFICIENT APPROACH FOR CREATING SPATIOTEMPORAL PREDICTIVE 3D MAPS OF LARGE-SCALE CULTURAL RESOURCES
    Doulamis, Anastasios
    Doulamis, Nikolaos
    Ioannidis, Charalabos
    Chrysouli, Christina
    Grammalidis, Nikos
    Dimitropoulos, Kosmas
    Potsiou, Chryssy
    Stathopoulou, Elisavet Konstantina
    Ioannides, Marinos
    [J]. 25TH INTERNATIONAL CIPA SYMPOSIUM 2015, 2015, : 61 - 68
  • [8] Super-resolution compressive imaging with anamorphic optics
    Farber, Vladimir
    August, Yitzhak
    Stern, Adrian
    [J]. OPTICS EXPRESS, 2013, 21 (22): : 25851 - 25863
  • [9] Hampton J, 2017, COMPRESSIVE SAMPLING
  • [10] Joint MAP registration and high-resolution image estimation using a sequence of undersampled images
    Hardie, RC
    Barnard, KJ
    Armstrong, EE
    [J]. IEEE TRANSACTIONS ON IMAGE PROCESSING, 1997, 6 (12) : 1621 - 1633