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Compressive sensing reconstruction of hyperspectral images based on codec space-spectrum joint dense residual network 期刊论文  OAI收割
Iet Image Processing, 2022, 页码: 16
作者:  
S. M. Xiao;  Y. Zhang;  X. L. Chang and J. J. Xu
  |  收藏  |  浏览/下载:1/0  |  提交时间:2023/06/14
Ship Detection Based on Compressive Sensing Measurements of Optical Remote Sensing Scenes 期刊论文  OAI收割
Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022, 卷号: 15, 页码: 8632-8649
作者:  
S. M. Xiao;  Y. Zhang and X. L. Chang
  |  收藏  |  浏览/下载:7/0  |  提交时间:2023/06/14
Hyperspectral imaging via a multiplexing digital micromirror device 期刊论文  OAI收割
Optics and Lasers in Engineering, 2022, 卷号: 151, 页码: 7
作者:  
W. Chen;  M. J. Sun;  W. J. Deng;  H. X. Hu;  L. J. Li and X. J. Zhang
  |  收藏  |  浏览/下载:12/0  |  提交时间:2023/06/14
Remote Sensing Image Compression in Visible Near-Infrared Range Using Heterogeneous Compressive Sensing 期刊论文  OAI收割
Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018, 卷号: 11, 期号: 12, 页码: 4932-4938
作者:  
Li, J.;  Fu, Y.;  Li, G. N.;  Liu, Z. L.
  |  收藏  |  浏览/下载:27/0  |  提交时间:2019/09/17
The Application of Biomimetic Lightweight Sandwich Panel to the Aircraft Structure with Large Cutout and Its Optimum Design 期刊论文  OAI收割
Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2017, 卷号: 53, 期号: 13
作者:  
Guo, C.;  Z. Lu and Y. Wu
  |  收藏  |  浏览/下载:9/0  |  提交时间:2018/06/13
Growth dynamics and carrier control of the third generation semiconductor with large mismatch and strong polarization 期刊论文  OAI收割
Faguang Xuebao/Chinese Journal of Luminescence, 2016, 卷号: 37, 期号: 11
作者:  
Wang, X.-Q.;  D.-B. Li;  B. Liu;  Q. Sun and J.-C. Zhang
收藏  |  浏览/下载:13/0  |  提交时间:2017/09/11
Fusion of infrared and visible images based on compressive sensing 期刊论文  OAI收割
Guangxue Jingmi Gongcheng/Optics and Precision Engineering, 2015, 卷号: 23, 期号: 3, 页码: 855-863
作者:  
Zhou, Y.-R.;  A.-H. Geng;  Q. Zhang;  J. Chen and Y.-X. Dong
收藏  |  浏览/下载:10/0  |  提交时间:2016/08/24
Image coding using wavelet-based compressive sampling (EI CONFERENCE) 会议论文  OAI收割
2012 5th International Symposium on Computational Intelligence and Design, ISCID 2012, October 28, 2012 - October 29, 2012, Hangzhou, China
作者:  
Li J.;  Li J.;  Li J.
收藏  |  浏览/下载:34/0  |  提交时间:2013/03/25
In this paper  we proposed a novel coding scheme is proposed using wavelet-based CS framework for nature image. First  two-dimension discrete wavelet transform (DWT) is applied to a nature image for sparse representation. After multi-scale DWT  the low-frequency sub-band and high-frequency sub-bands are re-sampled separately. According to the statistical dependences among DWT coefficients  we allocate different measurements to low- and high-frequency component. Then  the measurements samples can be quantized. The quantize samples are entropy coded and forward correct coding (FEC). Finally  the compressed streams are transmitted. At the decoder  one can simply reconstruct the image via l1 minimization. Experimental results show that the proposed wavelet-based CS scheme achieves better compression performance against the relevant existing solutions.