Codec Citra Berbasis Fractal dan Entropy Coding
Abstract
The process of describing parts of the human body, to be able to find any disease that exists in the body parts caused by bacteria and viruses is called the Medical Image. CT Scanning, MRI, X-Ray, is a medical image that is commonly found in general in the form of analog data. The amount of important information contained in medical images causes the size of the medical image file to be relatively large. The need for large data storage media and long delivery times is caused by large medical image data. This study aims to realize a fractal-based medical image codec by testing its performance on several coding entropy techniques. The analysis of this study was based on the PSNR, Image Size and Time Taken needed to compress one image. The conclusion obtained from this analysis shows that the Arithmetic method has more advantages in the field of PSNR, Compression Ratio, Size Image produced along with Time Taken in the compression process, where 15 images of 100% images are better results using the Arithmetic method than by using the Adaptive Huffman method.
Keywords — Adaptive Huffman, Arithmetic, Codec, Fractal, Image, Medical.
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 International License
