Bayesian-based binary compression with bandwidth optimisation for UAV aerial images
by Pankaj Agarwal; Sapna Yadav; J. Pradeep Kandhasamy; A. Balaji; S. Markkandan; D. Vijendra Babu
International Journal of Engineering Systems Modelling and Simulation (IJESMS), Vol. 15, No. 2, 2024

Abstract: This article proposes a new Bayesian-based binary compression model for UAV aerial pictures. This technique utilises inter-signal correlations to extract several sparse signals simultaneously. BKF-based approach employs both intra- and inter-signal correlations. The Bessel K-form (BKF) also features a higher zero peak with longer tails. Consumers may use UAV-borne base stations for temporary or emergency services. The effectiveness of low-bandwidth wireless Bayesian UAV communication BS still a challenge. This study's aim is to enhance UAV-BS spectrum usage while maintaining user fairness. Through aerial picture quality, we propose adjusting the distribution of bandwidth, power, and UAV-BS trajectory to capture the object image. The proposed method outperforms other approaches in aerial picture detection. To get high quality aerial images, Bayesian-based binary compression lowers picture size and minimises noise. The advantages of UAVs using the Bayesian approach have spurred research interest in novel communication systems.

Online publication date: Fri, 01-Mar-2024

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