Convergence Complexity Reduction for Block-based Compressive Sensing Reconstruction

2014 ◽  
Vol 19 (2) ◽  
pp. 240-249 ◽  
Author(s):  
Younggyun Park ◽  
Hiuk Jae Shim ◽  
Byeungwoo Jeon
Keyword(s):  
Compressive Sensing ◽  
Complexity Reduction ◽  
Block Based

CMOS Image Sensor With Area-Efficient Block-Based Compressive Sensing

2015 ◽  
Vol 15 (7) ◽  
pp. 3699-3710 ◽  
Author(s):  
Mohammadreza Dadkhah ◽  
M. Jamal Deen ◽  
Shahram Shirani
Keyword(s):  
Compressive Sensing ◽  
Cmos Image Sensor ◽  
Image Sensor ◽  
Block Based ◽  
Area Efficient

scholarly journals Rate Allocation for Block-based Compressive Sensing

2015 ◽  
Vol 20 (3) ◽  
pp. 398-407 ◽  
Author(s):  
Quang Hong Nguyen ◽  
Khanh Quoc Dinh ◽  
Viet Anh Nguyena ◽  
Chien Van Trinh ◽  
Younghyeon Park ◽  
...  
Keyword(s):  
Compressive Sensing ◽  
Rate Allocation ◽  
Block Based

Energy Efficiency and Reliability Considerations of a Compressive Sensing Technique in Wireless Visual Sensor Networks

2011 ◽  
pp. 21-39
Author(s):  
Yinhao Ding ◽  
Cheng-Chew Lim
Keyword(s):  
Energy Efficiency ◽  
Sensor Networks ◽  
Compressive Sensing ◽  
Visual Sensor ◽  
Haar Wavelet Transform ◽  
Visual Sensor Networks ◽  
Wireless Visual Sensor Networks ◽  
The Difference ◽  
Block Based ◽  
Efficiency And Reliability

This chapter focuses on the energy efficiency and reliability issues when applying the novel compressive sensing technique in wireless visual sensor networks. An explanation is given for why compressive sensing is useful for visual sensor networks. The relationships between sparsity control and compression ratio, the effect of block-based sampling on reconstruction quality, complexity consideration of reconstruction process for real-time applications, and compensation for packets missing in network flows are discussed. We analyse the effectiveness of using the 2-dimensional Haar wavelet transform for sparsity control, the difference between compressive sampling in spatial and frequency domains, and the computation of the prime-dual optimisation method and the log barrier algorithm for reconstruction. The effectiveness of the approach on recovered image quality is evaluated using Euclidean distance and variance analysis.

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