Autoencoder-based image compression for wireless sensor networks

This work presents an image compression technique designed for wireless sensor networks (WSNs), leveraging autoencoders and incorporating an error-bound mechanism. The algorithm strategically reduces redundancies in image data, conserving energy by exploiting spatial and temporal correlations within...

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Bibliographic Details
Published in:Scientific African 2024-06, Vol.24, p.e02159, Article e02159
Main Authors: Lungisani, Bose Alex, Zungeru, Adamu Murtala, Lebekwe, Caspar, Yahya, Abid
Format: Article
Language:English
Subjects:
Autoencoder
Compression ratio
Error-bound mechanism
Image compression
Image reconstruction quality
Wireless sensor networks
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Summary:This work presents an image compression technique designed for wireless sensor networks (WSNs), leveraging autoencoders and incorporating an error-bound mechanism. The algorithm strategically reduces redundancies in image data, conserving energy by exploiting spatial and temporal correlations within sampled image data through autoencoder features. Precise control over the distortion level in reconstructed images is achieved via the error-bound mechanism, establishing equilibrium between compression rate and reconstruction error. Evaluation results demonstrate comparable image reconstruction fidelity to existing methods (JPEG, JPEG2000, HDPhoto, and an existing Rate-Distortion Balanced approach). The proposed algorithm achieves superior image reconstruction quality at compression ratio rates exceeding 70%, emphasizing a fundamental approach prioritizing heightened reconstructed image quality while balancing compression ratio, distortion, and energy efficiency. Notably, a substantial 50% reduction in overall energy consumption is realized at a compression rate of 38.6%.
ISSN:2468-2276
2468-2276
DOI:10.1016/j.sciaf.2024.e02159