A multilayer improved RBM network based image compression method in wireless sensor networks

The processing capacity and power of nodes in a Wireless Sensor Network (WSN) are limited. And most image compression algorithms in WSN are subject to random image content changes or have low image qualities after the images are decoded. Therefore, an image compression method based on multilayer Res...

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Veröffentlicht in:International journal of distributed sensor networks Jg. 2016
Hauptverfasser: Cheng, Chunling, Wang, Shu, Chen, Xingguo, Yang, Yanying
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Sage Publications Ltd. (UK) 01.01.2016
Schlagworte:
Algorithms
Analysis
Applied research
Data compression
Methods
Optimization theory
Wireless sensor networks
ISSN:1550-1329
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Abstract The processing capacity and power of nodes in a Wireless Sensor Network (WSN) are limited. And most image compression algorithms in WSN are subject to random image content changes or have low image qualities after the images are decoded. Therefore, an image compression method based on multilayer Restricted Boltzmann Machine (RBM) network is proposed in this paper. The alternative iteration algorithm is also applied in RBM to optimize the training process. The proposed image compression method is compared with a region of interest (ROI) compression method in simulations. Under the same compression ratio, the qualities of reconstructed images are better than that of ROI. When the number of hidden units in top RBM layer is 8, the peak signal-to-noise ratio (PSNR) of the multilayer RBM network compression method is 74.2141, and it is much higher than that of ROI which is 60.2093. The multilayer RBM based image compression method has better compression performance and can effectively reduce the energy consumption during image transmission in WSN.
AbstractList The processing capacity and power of nodes in a Wireless Sensor Network (WSN) are limited. And most image compression algorithms in WSN are subject to random image content changes or have low image qualities after the images are decoded. Therefore, an image compression method based on multilayer Restricted Boltzmann Machine (RBM) network is proposed in this paper. The alternative iteration algorithm is also applied in RBM to optimize the training process. The proposed image compression method is compared with a region of interest (ROI) compression method in simulations. Under the same compression ratio, the qualities of reconstructed images are better than that of ROI. When the number of hidden units in top RBM layer is 8, the peak signal-to-noise ratio (PSNR) of the multilayer RBM network compression method is 74.2141, and it is much higher than that of ROI which is 60.2093. The multilayer RBM based image compression method has better compression performance and can effectively reduce the energy consumption during image transmission in WSN.
Audience Academic
Author Wang, Shu
Chen, Xingguo
Yang, Yanying
Cheng, Chunling
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SubjectTerms Algorithms
Analysis
Applied research
Data compression
Methods
Optimization theory
Wireless sensor networks
Title A multilayer improved RBM network based image compression method in wireless sensor networks
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