Performance Evaluation of Wavelet based Image Compression Techniques for Wireless Multimedia Sensor Networks

Abstract

The availability of advanced low cost hardware devices such as micro-electro-mechanical system
(MEMS) based camera sensors technology, low power analog and digital electronics, and low power radio frequency
(RF) integrated circuits design has led to the development of wireless multimedia sensor networks (WMSNs) to
communicate multimedia information such as audio, video and still images from the environment for a wide range
of applications like video surveillance, automated assistance for elderly, environmental monitoring, industrial
process control, and advanced health care delivery. Sensor nodes in wireless sensor networks have very limited
resources such as low memory capacity, low processing capability, and low data rate or limited wireless channel
bandwidth. Energy consumption is also one of the critical problems which affect the lifetime of wireless sensor
networks as the sensor nodes are battery operated. Image compression is one of the techniques to reduce the energy
consumption of such sensor nodes to increase the life time of sensor networks. In this paper, we have evaluated
performance parameters of image compression like PSNR, CR, processing time, and memory consumption using
three image coding techniques (EZW, SPIHT, and SPECK) and lifting-based discrete wavelet transform (CDF 9/7).
The experimental results show the overall performance of SPIHT algorithm is better than the other compression
techniques for low bit rates < 1 bpp.