Multimedia Tools and Applications

, Volume 77, Issue 23, pp 30187–30203 | Cite as

Energy efficient surveillance system using WVSN with reweighted sampling in modified fast Haar wavelet transform domain

  • R. MonikaEmail author
  • R. Hemalatha
  • S. Radha


Wireless visual sensor network (WVSN) consists of a large number of nodes that are capable of acquiring, compressing and transmitting images. Surveillance becomes a vital application area of WVSN as they can be deployed in various environments to monitor and collect information. The lifetime of the nodes in the network depends on the energy consumption. Hence in this paper, block compressed sensing (BCS) based image transmission technique that utilizes Energy based Reweighted sampling (ERWS) in Modified Fast Haar Wavelet Transform (MFHWT) domain is proposed to reduce energy consumption considerably. Sparse binary random matrix is used to acquire CS measurements in MFHWT domain. In addition, the proposed technique also maintains the image quality. The developed algorithm is applied and tested for a car parking lot monitoring system. It is evident from the simulation results that the proposed method achieves better PSNR values even for fewer measurements. Experimental analysis is performed using Atmega 128 processor of Mica mote in WinAVR by Atmel. The proposed method has approximately 85.5% lesser energy consumption than other Compressed Sensing (CS) methods. Lossless Entropy Coding is applied to the ERWS measurements and considerable reduction in number of transmitted bits is also achieved. The algorithm has also been tested in WINGZ mote in real time.


WVSN CS ERWS MFHWT DCT RWS Sparse Binary random matrix 


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Electronics and CommunicationSRM UniversityKattankulathurIndia
  2. 2.Department of Electronics and CommunicationSSN College of EngineeringChennaiIndia

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