Low Complexity Distributed Video Coding Using Compressed Sensing

سال انتشار: 1392
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 1,264

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شناسه ملی سند علمی:

ICMVIP08_194

تاریخ نمایه سازی: 9 بهمن 1392

چکیده مقاله:

Compressive sensing (CS) is an efficient method toreconstruct sparse images with under-sampled data. In thismethod sensing and coding steps integrated to a one-step, lowcomplexitymeasurement acquisition system. In this paper, weuse a Non-linear Conjugate Gradient (NLCG) algorithm tosignificantly increase the quality of reconstructed frames of videosequences. Our proposed framework divides sequence of a videoto several groups of pictures (GOPs), where each GOP consistingof one key frame followed by two non-key frames. CS is thenapplied on each key and non-key frame with different samplingrates. For reconstruction final frames, NLCG algorithm wasperformed on each key frame with acceptable fidelity. To achievedesired quality on low-rate sampled non-key frames, NLCGmodified using side information (SI) obtained from last twosuccessive reconstructed key frames. Based on some performancemeasures such as SNR, PSNR, SSIM and RSE, ourimplementation results indicate that employing NLCG withGaussian sampling matrix outperforms other methods in qualitymeasures.

کلیدواژه ها:

compressed sensing (CS) ، distributed video coding DVC) ، sparse reconstruction ، nonlinear conjugate gradient (NLCG)

نویسندگان

Samad Roohi

Dept. of Computer Arts -Islamic Art University of Tabriz

Majid Noorhosseini

Dept. of Computer Engineering and Information Technology -Amirkabir University of Technology

Jafar Zamani

Dept. of Biomedical Engineering -Amirkabir University of Technology,

Hamidreza Salighe Rad

Dept. of Medical Physics and Biomedical Engineering Tehran University of Medical Science And Research Center for Science and Technology i

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  • M. F. Duarte, M. A. Davenport, D. Takhar, J. N. ...
  • E. J. Candes, "Compressive sampling, " in Proceedings on the ...
  • 16th IEEE International Conference on, pp. 1393-1396, 2009. ...
  • Ihternational Conference on, pp. 1 169-1172, 2009 ...
  • M. A. T. Figueiredo, R. _ Nowak, and S. J. ...
  • M. Lustig, D. Donoho, and J. M. Pauly, "Sparse MRI: ...
  • C. E. Shannon, _ _ ommunication in the presence of ...
  • _ _ Theory, IEEE ...
  • E. J. Candes and T Tao, "Near-optimal signal recovery from ...
  • S. Chen and D. Donoho, "Basis pursuit, " in Signals, ...
  • _ _ _ linear systems, " ...
  • R. G. Baraniuk, "Compressive sensing [lecture notes], " Signal ...
  • _ _ _ for partial differential equations, " Applied Mathematics ...
  • _ Tran, "Fast _ scrambled block Hadamard ensemble, " preprint, ...
  • D. Baron, M. B. Wakin, M. F. Duarte, S. Sarvotham, ...
  • L. I. Rudin, S. Osher, and E. Fatemi, "Nonlinear total ...
  • نمایش کامل مراجع