12 August 2013 Low-complex energy-aware image communication in visual sensor networks
Yesudhas A. Phamila, Ramachandran Amutha
Author Affiliations +
Abstract
A low-complex, low bit rate, energy-efficient image compression algorithm explicitly designed for resource-constrained visual sensor networks applied for surveillance, battle field, habitat monitoring, etc. is presented, where voluminous amount of image data has to be communicated over a bandwidth-limited wireless medium. The proposed method overcomes the energy limitation of individual nodes and is investigated in terms of image quality, entropy, processing time, overall energy consumption, and system lifetime. This algorithm is highly energy efficient and extremely fast since it applies energy-aware zonal binary discrete cosine transform (DCT) that computes only the few required significant coefficients and codes them using enhanced complementary Golomb Rice code without using any floating point operations. Experiments are performed using the Atmel Atmega128 and MSP430 processors to measure the resultant energy savings. Simulation results show that the proposed energy-aware fast zonal transform consumes only 0.3% of energy needed by conventional DCT. This algorithm consumes only 6% of energy needed by Independent JPEG Group (fast) version, and it suits for embedded systems requiring low power consumption. The proposed scheme is unique since it significantly enhances the lifetime of the camera sensor node and the network without any need for distributed processing as was traditionally required in existing algorithms.
© 2013 SPIE and IS&T 0091-3286/2013/$25.00 © 2013 SPIE and IS&T
Yesudhas A. Phamila and Ramachandran Amutha "Low-complex energy-aware image communication in visual sensor networks," Journal of Electronic Imaging 22(4), 041107 (12 August 2013). https://doi.org/10.1117/1.JEI.22.4.041107
Published: 12 August 2013
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CITATIONS
Cited by 8 scholarly publications.
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KEYWORDS
Image compression

Image transmission

Image sensors

Visual communications

Sensor networks

Cameras

Image processing

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