Bayesian-based binary compression with bandwidth optimisation for UAV aerial images

Agarwal, Pankaj and Yadav, Sapna and Kandhasamy, J. Pradeep and Balaji, A. and Markkandan, S. and Babu, D. Vijendra (2024) Bayesian-based binary compression with bandwidth optimisation for UAV aerial images. INTERNATIONAL JOURNAL OF ENGINEERING SYSTEMS MODELLING AND SIMULATION, 15.0 (2). ISSN 1755-9758

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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.

Item Type: Article
Uncontrolled Keywords: Bayesian method, binary compression, bandwidth optimisation, UAV aerial images, Bessel K-form, BKF
Subjects: Engineering > Engineering
Multi-Disciplinary Studies > Multidisciplinary
Divisions: Engineering and Technology > Aarupadai Veedu Institute of Technology, Chennai, India > Computer Science and Engineering
Engineering and Technology > Aarupadai Veedu Institute of Technology, Chennai, India > Electronics and Communication Engineering
Depositing User: Unnamed user with email techsupport@mosys.org
Last Modified: 06 Feb 2026 07:14
URI: https://ir.vmrfdu.edu.in/id/eprint/7241

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