Medical Image Compression Techniques with Wavelet Discrete Transformation and Entropy Encoding

Teknik Kompresi Citra Medis dengan Transformasi Diskrit Wavelet dan Pengkodean Entropy

  • I Dewa Gede Hardi Rastama Universitas Udayana
  • I Made Oka Widyantara
  • Linawati
Keywords: citra medis, discrete wavelet transform, adaptive threshold


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.


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How to Cite
I Dewa Gede Hardi Rastama, I Made Oka Widyantara, & Linawati. (2020). Medical Image Compression Techniques with Wavelet Discrete Transformation and Entropy Encoding. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 4(1), 155 - 162.
Artikel Teknologi Informasi