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Dr. Sٍٍawsan Abdellatif Elsayed :: Publications:

Title:
Model-based quantization for perceptually weighted compressed video sensing
Authors: S. Elsayed, M. Elsabrouty, O. Muta, H. Furukawa
Year: 2016
Keywords: Not Available
Journal: IEICE Communications Express (ComEX)
Volume: 5
Issue: 7
Pages: 216-222
Publisher: Not Available
Local/International: International
Paper Link:
Full paper Not Available
Supplementary materials Not Available
Abstract:

Exploiting perceptual-based weighting can improve the reconstruction quality for compressed video sensing (CVS). Nevertheless, practical implementation of the compressed sensing (CS) requires quantizing the measurements. We propose a simplified sampling rate model for the perceptual CVS to achieve compromise between the number of measurements and the quantization bit-depth, which are the main contributing factors in the CS rate-distortion (RD) performance. The proposed model can achieve near optimal RD-performance obtained through exhaustive simulations. In addition, simulation results show that the quantized perceptual CVS achieve remarkable RD-performance gain, with lower sampling rate, compared to applying the quantization model on the standard CS.

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