Have a personal or library account? Click to login

Multi-Scale Compressed Sensing Based On Split Augmented Lagrangian Shrinkage Algorithm For Image Super-Resolution Reconstruction

By:
Open Access
|Jun 2016

References

  1. Donoho D L, “Compressed sensing”, IEEE Transactions on Information Theory, vol. 52, No. 4, 2006, pp. 1289-1306.10.1109/TIT.2006.871582
  2. Daode Zhang,Yangliu Xue,Xuhui Ye, Yanli Li,”Research On Chips’ Defect Extraction Based On Image-matching “, International Journal on Smart Sensing and Intelligent Systems (S2IS), Mar 10. 2014, pp. 321-336.10.21307/ijssis-2017-658
  3. Tsaig Y, Donoho D L, “Extensions of compressed sensing”, Signal Processing,vol. 86, No. 3,2006, pp. 533-548.10.1016/j.sigpro.2005.05.028
  4. James E. Fowler, Sungkwang Mun, and Eric W. Tramel,”Multi-scale block compressed sensing with smoothed projected landweber reconstruction”, 19th European Signal Processing Conference, Barcelona, Spain,2011.
  5. Feng LUO, Fengjian HU,”A Comprehensive Survey Of Vision Based Vehicle Intelligent Front Light System”,International Journal on Smart Sensing and Intelligent Systems (S2IS), June 1. 2014, pp. 701-723.10.21307/ijssis-2017-677
  6. Pu Jian,Zhang Junping,” Super-Resolution through Dictionary Learning and Sparse Representation”,[J].pattern recognition and artificial intelligence, 2010,pp. 335-340.
  7. Guohui Wu, Xingkun Li, Jiyang Dai.”Improved Measure Algorithm Based On CoSaMP For Image Recovery “,International Journal on Smart Sensing and Intelligent Systems (S2IS), June 1. 2014, pp. 724739.
  8. Candes E, Romberg J,” Sparsity and incoherence in compressive sampling”,[J]. Inverse Problems, vol. 23, No. 3, 2007, pp. 969-985.10.1088/0266-5611/23/3/008
  9. Ahadul Imam, Justin Chi, Mohammad Mozumdar,”Data Compression And Visualization For Wireless Sensor Networks “,International Journal on Smart Sensing and Intelligent Systems (S2IS),Dec 1. 2015, pp. 2083-2115.10.21307/ijssis-2017-844
  10. Payman Moallem1,”Compensation Of Capacitive Differential Pressure Sensor Using Multi Layer Perceptron Neural Network”, International Journal on Smart Sensing and Intelligent Systems (S2IS), Sep I. 2015, pp. 1443-1463.10.21307/ijssis-2017-814
  11. M. Afonso, J. Bioucas-Dias, M. Figueiredo, “Fast image recovery using variable splitting and constrained optimization”,[J]. IEEE Transactions on Signal Processing, vol. 19, No. 9, 2010, pp. 2345-235.10.1109/TIP.2010.204791020378469
  12. Guo K and Labate D, “Optimally Sparse multidimensional representation using shearlets “,SIAM J. Math. Anal, Vol. 39, 2007, pp. 298-318.10.1137/060649781
  13. Easley G, Labate D, Lim W.”Sparse Directional image representations using the discrete Shearlet transform”, [J].Applied and Computational Harmonic Analysis, vol. 25,2008, pp. 25-46.10.1016/j.acha.2007.09.003
  14. Do T T, Tran T D, Lu G, “Fast compressive sampling with structurally random matrices” Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing. Washington D C: IEEE Computer Society Press, 2008, pp. 3369-3372.10.1109/ICASSP.2008.4518373
  15. Chen SSB, Donoho D L, M A Saunders, “Atomic decomposition by basis pursuit”, [J]. SIAM Journal on Scientific Computation, vol. 20, No. 1, 1998, pp. 33-61.10.1137/S1064827596304010
  16. Tropp J A. Greed is good, ‘‘Algorithmic results for sparse approximation”,[J]. IEEE Transactions on Information Theory, vol. 50, No. 10, 2004, pp. 2231-2242.10.1109/TIT.2004.834793
  17. Blumensath T, Davies M E, ‘Normalised iterative hard thresholding:guaranteed stability and performance”,[J],IEEE Journal of Selected Topics in Signal Processing, vol. 4, No. 2,2010, pp. 298-309.10.1109/JSTSP.2010.2042411
  18. Wenqing Chen, 2 Tao Wang and 3 Bailing Wang, ‘Design Of Digital Image Encryption Algorithm Based On Mixed Chaotic Sequences” International Journal on Smart Sensing and Intelligent Systems (S2IS), Dec. 1. 2014, pp. 1453-1469.10.21307/ijssis-2017-715
  19. Yongqing Wang1* and Xiling Liu, “Face Recognition Based On Improved Support Vector Clustering “,International Journal on Smart Sensing and Intelligent Systems (S2IS), Dec. 1. 2014, pp. 1807-1829.10.21307/ijssis-2017-734
  20. Qu Xiao-Bo, Yan Jing-Wen, Zhu Zi-Qian, Chen Ben-Gang. “Multipulse coupled neural networks”. In Proceedings of International Conference on Bio-Inspired Computing Theories and Applications. Zhengzhou, China: Publishing House of Electronics Industry. 2007,pp.563-565.
  21. Sen P,Darabi S,”Compressive image super-resolution”, Proceedings of Signals, Systems and Computers. Los Alamitos:IEEE Computer Society Press,2009,pp. 1235-1242.10.1109/ACSSC.2009.5469968
  22. Yang C, Wright J, Huang T, Ma Y,”Image super-resolution via sparse representation”,[J].IEEE Trans. Image Process, vol. 19, No. 11, 2010.pp. 2861-2873.10.1109/TIP.2010.205062520483687
  23. J. Bioucas-Dias, M. Figueiredo,”A new TwIST: Two-step iterative shrinkage/thresholding algorithms for image restoration”, [J]. IEEE Transactions on Image Processing, vol. 16, No. 12, 2007, pp. 2992-3004.10.1109/TIP.2007.90931918092598
  24. A. Beck, M. Teboulle,”A fast iterative shrinkage-thresholding algorithm for linear inverse problems”, [J]. SIAM Journal on Imaging Sciences, vol. 2, No. 1, 2009, pp. 183-202.10.1137/080716542
Language: English
Page range: 563 - 579
Submitted on: Dec 16, 2015
Accepted on: Mar 21, 2016
Published on: Jun 1, 2016
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 times per year

© 2016 Tian Shu-yao, Hu Chun-hai, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.