Rizalafande Che Ismail
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Rizalafande Che Ismail
Official Name
Rizalafande, Che Ismail
Alternative Name
Ismail, Rizalafande C.
Rizalafande, Che Ismail
Chesmail, R.
Ismail, R. C.
Che Ismail, Rizalafande
Ismail, Rizalafande Che
Ismail, R. Che
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Scopus Author ID
22634128600

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  • Publication
    Image data compression using discrete cosine transform technique for wireless transmission
    ( 2021-12)
    Mona H. Haron
    ;
    Mohd Nazrin Md Isa
    ;
    Muhammad Imran Ahmad
    ;
    Rizalafande Che Ismail
    ;
    Norhawati Ahmad
    Telemetry data transfer over long-range wireless network for internet of things-based applications presently gaining popularity and this trend continuous in the era of Industrial Revolution (IR 4.0). However, transmitting larger amount of data such as images is a challenging task and requires further attention and research. Moreover, transmitting data over open agricultural area requires this capability to collect field data for further research and analysis. This work aims to propose a suitable image compression technique and recommends for the best compression ratio as to address the aforementioned issue. Discrete Cosine Transform (DCT) is a well-known lossy-based image compression technique, which has been explored along with another compression algorithm known as Fast Fourier Transform (FFT). Comparison between the two most widely used compression algorithms was analyzed and discussed. In this paper, golden apple snail images are acquired from various databases which include the mature snail, adult female laying eggs, snail pink eggs on stem and snails in the water. A MATLAB code is written to implement both algorithms with input images from the database is tested on the developed algorithm. Simulation results have shown that the input images can be compressed with a different value of compression ratio (CR) ranging from 3.00 to 50.00. Other than that, it is noted that the quality of the compression ratio is 49.04 with Mean Square Error (MSE) of 172.72 and Peak Signal to Noise Ratio (PSNR) of 25.75.