Adaptive image compression for vehicular ad hoc networks: a discrete wavelet transform low-low subband (DWT-LL), singular value decomposition (SVD), and linear programming (LP) approach for vehicle density sensing-based compression

Mfon Okpok; Billy Kihei

doi:10.1117/12.3013968

7 June 2024 Adaptive image compression for vehicular ad hoc networks: a discrete wavelet transform low-low subband (DWT-LL), singular value decomposition (SVD), and linear programming (LP) approach for vehicle density sensing-based compression

Mfon Okpok, Billy Kihei

Author Affiliations +

Proceedings Volume 13052, Autonomous Systems: Sensors, Processing, and Security for Ground, Air, Sea, and Space Vehicles and Infrastructure 2024; 130520D (2024) https://doi.org/10.1117/12.3013968
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Abstract

This research presents a novel technique for image compression and transmission tailored for Vehicular Ad Hoc Networks (VANETs), emphasizing the adaptation of Modulation and Coding schemes (MCS) to suit compression ratio demands contingent on vehicle density around roadside units. Leveraging Discrete Wavelet Transform Low-Low subband (DWT LL), Singular Value Decomposition (SVD), and Linear Programming (LP), the proposed technique dynamically adjusts compression ratios based on vehicular presence. Consequently, it enables simultaneous modulation of MCS and image compression, uniquely customizing images for VANET applications. Compression ratios ranging from 47.01% to 74.1% are achieved, correlating with vehicle density near Roadside units, satisfying size constraints crucial for efficient Infrastructure to Vehicles (I2V) image message dissemination within a 300-meter radius accommodating up to 200 vehicles. This adaptive approach holds promise for delivering image-enhanced public emergency notifications within the transportation sector, offering a viable solution for real-time communication and enhancing situational awareness amidst dynamic vehicular environments.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Mfon Okpok and Billy Kihei "Adaptive image compression for vehicular ad hoc networks: a discrete wavelet transform low-low subband (DWT-LL), singular value decomposition (SVD), and linear programming (LP) approach for vehicle density sensing-based compression", Proc. SPIE 13052, Autonomous Systems: Sensors, Processing, and Security for Ground, Air, Sea, and Space Vehicles and Infrastructure 2024, 130520D (7 June 2024); https://doi.org/10.1117/12.3013968

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