Paper Info
Title
Highly Reliable and Low-Complexity Image Compression Scheme Using Neighborhood Correlation Sequence Algorithm in WSN
Abstract
Recently, the advancements in the field of wireless technologies and micro-electro-mechanical systems lead to the development of potential applications in wireless sensor networks (WSNs). The visual sensors in WSN create a significant impact on computer vision based applications such as pattern recognition and image restoration. generate a massive quantity of multimedia data. Since transmission of images consumes more computational resources, various image compression techniques have been proposed. But, most of the existing image compression techniques are not applicable for sensor nodes due to its limitations on energy, bandwidth, memory, and processing capabilities. In this article, we introduce a highly reliable and low-complexity image compression scheme using neighborhood correlation sequence (NCS) algorithm. The NCS algorithm performs the bit reduction operation and then encoded by a codec (such as PPM, Deflate, and Lempel Ziv Markov chain algorithm.) to further compress the image. The proposed NCS algorithm increases the compression performance and decreases the energy utilization of the sensor nodes with high fidelity. Moreover, it achieved a minimum end to end delay of 1074.46 ms at the average bit rate of 4.40 bpp and peak signal to noise ratio of 48.06 on the applied test images. On comparing with state-of-art methods, the proposed method maintains a better tradeoff between compression efficiency and reconstructed image quality.
Year
DOI
Venue
2020
10.1109/TR.2020.2972567
IEEE Transactions on Reliability
Keywords
DocType
Volume
High fidelity,image compression,Lempel Ziv Markov chain algorithm (LZMA),reliability,source coding,wireless sensor networks (WSNs)
Journal
69
Issue
ISSN
Citations 
4
0018-9529
2
PageRank 
References 
Authors
0.37
21
3
Name
Order
Citations
PageRank
J. Uthayakumar131.05
mohamed elhoseny258349.57
K. Shankar39513.88