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Analisis Kualitas Citra Medis Terkompresi JPEG Derry Suia Pathentantama; I Made Oka Widyantara; Rukmi Sari Hartati
Jurnal Teknologi Elektro Vol 18 No 2 (2019): (Mei-Agustus) Majalah Ilmiah Teknologi Elektro
Publisher : Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (240.89 KB) | DOI: 10.24843/MITE.2019.v18i02.P12

Abstract

Basically, image compression technology is a basic step to compress images so that they can be transmitted more quickly and save storage space in storage media. This is a breakthrough that was created in 1920. This research is applied research that focuses on the application of JPEG algorithms based on the value of PSNR. This study uses X-Ray image data as input data, where the image will be searched for the optimal compression ratio of 9 compression ratios (10% -90%). A total of 10 test data were used. From the table results of system testing using test images, it can be seen that the characteristics of PSNR are able to determine the compression ratio of medical images optimally. and the higher the image compression ratio applied to the test image, the higher the quality of the reconstructed image. This can be seen in the PSNR value table, where the PSNR value increases in each compression ratio.
Analisis Kualitas Citra Medis Terkompresi JPEG Derry Suia Pathentantama; I Made Oka Widyantara; Rukmi Sari Hartati
Jurnal Teknologi Elektro Vol 18 No 2 (2019): (Mei-Agustus) Majalah Ilmiah Teknologi Elektro
Publisher : Program Studi Magister Teknik Elektro Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MITE.2019.v18i02.P12

Abstract

Basically, image compression technology is a basic step to compress images so that they can be transmitted more quickly and save storage space in storage media. This is a breakthrough that was created in 1920. This research is applied research that focuses on the application of JPEG algorithms based on the value of PSNR. This study uses X-Ray image data as input data, where the image will be searched for the optimal compression ratio of 9 compression ratios (10% -90%). A total of 10 test data were used. From the table results of system testing using test images, it can be seen that the characteristics of PSNR are able to determine the compression ratio of medical images optimally. and the higher the image compression ratio applied to the test image, the higher the quality of the reconstructed image. This can be seen in the PSNR value table, where the PSNR value increases in each compression ratio.