Similarity Comparison of the Packet Wavelet Transform Method for Medical Image Compression

Atmaja, I Made Ari Dwi Suta (2023) Similarity Comparison of the Packet Wavelet Transform Method for Medical Image Compression. Politeknik Negeri Padang. (Submitted)

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Abstract

Medical images are often used for educational, analytical, and medical diagnostic purposes. Medical image data requires large amounts of storage on computers. Three types of codecs, namely Haar, Daubechies, and Biorthogonal, were used in this study. This study aims to find the best wavelet method of the three tested wavelet methods (Haar, Daubechies, and Biorthogonal). This study uses medical images representing USG and CT-scan images as testing data. The first test is carried out by comparing the threshold ratio. Three threshold values are used, namely 30, 40, and 50. The second test looks for PSNR values with different thresholds. The third test looks for a comparison of the rate (image size) to the PSSR value. The final test is to find each medical image's compression and decompression times. The first compression ratio test results on both medical images showed that CT scan images on Haar and Biorthogonal wavelets were the best, with an average compression ratio of 40.76% and a PSNR of 33.77. The PSNR obtained is also getting more significant for testing with a larger image size. The average compression time is 0.52 seconds, and the decompression time is 2.27 seconds. Based on the test results, this study recommends that the Daubechies wavelet method is very good for compression, which is 0.51 seconds, and the Biorthogonal wavelet method is very good for medical image decompression, which is 1.69 seconds.

Item Type: Other
Subjects: Ilmu Teknik > Teknik Elektro Dan Informatika > Teknologi Informasi
Divisions: Jurusan Teknologi Informasi > Prodi D2 Administrasi Jaringan Komputer > Publikasi
Depositing User: I Made Ari Dwi Suta Atmaja
Date Deposited: 19 Jun 2024 07:57
Last Modified: 19 Jun 2024 07:57
URI: http://repository.pnb.ac.id/id/eprint/10725

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