Teknik Kompresi Citra Medis dengan Transformasi Diskrit Wavelet dan Pengkodean Entropy

Medical imaging is a presentment of human organ parts. Medical imaging is saved on a film; therefore, it needs a big saving quota. Compressing is a process to remove redundancy from a piece of information without reducing its quality. This study recommended compressed medical image with DWT (Discret...

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Bibliographic Details
Main Authors: I Dewa Gede Hardi Rastama, I Made Oka Widyantara, Linawati
Format: Article
Language:English
Published: Ikatan Ahli Informatika Indonesia 2020-02-01
Series:Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Subjects:
Online Access:http://jurnal.iaii.or.id/index.php/RESTI/article/view/1487
Description
Summary:Medical imaging is a presentment of human organ parts. Medical imaging is saved on a film; therefore, it needs a big saving quota. Compressing is a process to remove redundancy from a piece of information without reducing its quality. This study recommended compressed medical image with DWT (Discrete Wavelet Transform) with adaptive threshold added and entropy copying with the Run Length Encoding (RLE) coding. This study is comparing several parameters, such as compressed ratio and compressed image file size, and PSNR (Peak Signal to Noise Ratio) for analyzing the quality of reconstructive image. The study showed that the comparison of rate, compressed ratio, and PSNR tracing of Haar and Daubechies doesn’t have a significant difference. Comparison of rate, compressed ratio, and PSNR tracing on the hard and soft threshold is the rate of the sold threshold is lower than the hard threshold. The optimal outcome of this study is to use a soft threshold.
ISSN:2580-0760