Enhancing Real-Time Image Transmission in Wireless Sensor Networks: A Study on Energy-Efficient Compression Algorithms

The pervasive usage of Wireless Sensor Networks (WSNs) across various sectors - including environmental monitoring, intelligent transportation, healthcare, and security surveillance necessitates efficient mechanisms for real-time image transmission. The ability to deliver timely and accurate visual information is essential for effective decision-making in these applications. Current techniques for real-time image transmission and compression in WSNs, unfortunately, fail to adequately consider the energy limitations of sensor nodes, often leading to premature energy exhaustion and consequently destabilizing the network's overall reliability. This study presents an investigation into an innovative joint encoding strategy for real-time image transmission and compression in WSNs, proposed to address these limitations. When compared with decoding schemes individually optimized for each user's channel conditions, it is demonstrated that the proposed method achieves a comparable quality of image reconstruction. Furthermore, this study introduces a postprocessing network model, designed to mitigate compression artifacts, facilitating superior image reconstruction quality even at high compression ratios and low bit rates. Experimental results underscore the effectiveness of this new approach.