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  5. Image data compression using fast Fourier transform (FFT) technique for wireless sensor network
 
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Image data compression using fast Fourier transform (FFT) technique for wireless sensor network

Journal
AIP Conference Proceedings
ISSN
0094243X
Date Issued
2024-02-08
Author(s)
Haron M.H.
Mohd Nazrin Md Isa
Universiti Malaysia Perlis
Muhammad Imran Ahmad
Universiti Malaysia Perlis
Arshad M.A.M.
Asral Bahari Jambek
Universiti Malaysia Perlis
Siti Zarina Md Naziri
Universiti Malaysia Perlis
Hussin R.
Harun A.
Rizalafande Che Ismail
Universiti Malaysia Perlis
Shaiful Nizam Mohyar
Universiti Malaysia Perlis
DOI
10.1063/5.0195298
Abstract
Agricultural settings present unique challenges for the transmission of huge amounts of images over long-range wireless networks. It is challenging to remotely gather data for transmission over a wireless network in research areas due to a lack of basic amenities like internet connections, especially in distant agricultural areas. In this research, the Fast Fourier Transform (FFT) method was used in conjunction with the Discrete Cosine Transform (DCT) method of image compression to achieve a higher compression ratio. In order for a Wireless Sensor Network (WSN) to provide compressed image data to a wireless based station, a LoRaWAN network has been identified. Low-power LoRaWAN networks may regularly transmit compressed images from an agricultural region to a monitoring system up to 15 km away. Images of golden apple snails were collected for this study from a variety of sources. The procedure was coded in MATLAB so that it could be run with input images being judged by the created algorithm. The input images can be compressed with a range of compression ratios (CR) from 3.00 to 50.00, as shown by the simulation results. Compressed image quality is measured not only by the above-mentioned criteria, but also by Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR). According to the numbers, the best achievable compression ratio is 49.04, with an MSE of 172.72 and a PSNR of 25.75 at its highest.
File(s)
Research repository notification.pdf (4.4 MB)
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