Izvorni znanstveni članak
https://doi.org/10.1080/00051144.2024.2312747
Effective hybrid video denoising and blending framework for Internet of Remote Things (IoRT) environments
B. Aruna Devi
; Department of Electronics and Communication Engineering, Dr. N.G.P. Institute of Technology, Coimbatore, India
Mani Deepak Choudhry
; Department of Information Technology, KGiSL Institute of Technology, Coimbatore, India
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* Dopisni autor.
Sažetak
The Internet of Remote Things (IoRT) has emerged as a transformative paradigm, merging IoT
capabilities with remote technologies. IoRT environments, featuring interconnected sensors
and robots, face challenges like sensor noise and low-light conditions, compromising video
stream quality. This paper proposes a Hybrid Video Denoising and Blending Framework to
address IoRT video data shortcomings. Leveraging spatial and temporal domain denoising techniques, the framework effectively removes noise while preserving crucial details. The inclusion
of advanced blending algorithms facilitates seamless fusion of data from multiple sources,
enhancing decision-making in real-world scenarios. The framework adopts a dynamic weighted
averaging approach and an optimal sensor selection mechanism to intelligently choose informative data sources, improving blended output quality. Extensive experiments with a diverse
IoRT dataset showcase the framework’s superiority over state-of-the-art techniques, offering significant enhancements in video quality, noise reduction, and data fusion accuracy. Applications
like surveillance, autonomous remotes, and industrial automation can benefit from the framework’s ability to provide clearer, more reliable visual information. In conclusion, this research
introduces a pioneering approach to mitigate video noise and enhance data fusion in IoRT, showcasing promising results and paving the way for further research in the integration of Remotes
and IoT.
Ključne riječi
Internet of Remote Things (IoRT); real-time processing; noise reduction; video quality enhancement; visual data processing; reliability and accuracy
Hrčak ID:
323043
URI
Datum izdavanja:
2.2.2024.
Posjeta: 0 *