Analisis Kinerja Dan Kualitas Hasil Kompresi Pada Citra Medis Sinar-X Menggunakan Algoritma Huffman, Lempel Ziv Welch Dan Run Length Encoding

Abstract

Technological progress in the medical area made medical images like X-rays stored in digital files. The medical image file is relatively large so that the image needs to be compressed. The lossless compression technique is an image compression where the decompression results are the same as the original or no information lost in the compression process. The existing algorithms on lossless compression techniques are Run Length Encoding (RLE), Huffman, and Lempel Ziv Welch (LZW). This study compared the performance of the three algorithms in compressing medical images. The result of image decompression will be compared to its performance in the objective assessment such as ratio, compression time, MSE (Mean Square Error) and PNSR (Peak Signal to Noise Ratio). MSE and PSNR are used for quantitative image quality measurement for subjective assessment assisted by three experts who will compare the original image with the decompression image. Based on the results obtained from the objective assessment of compression performance of RLE algorithm showed the best performance by yielding ratio, time, MSE and PSNR respectively 86,92%, 3,11ms, 0 and 0db. For Huffman, the results can be 12.26%, 96.94ms, 0, and 0db respectively. While LZW results can be in sequence -63.79%, 160ms, 0.3 and 58.955db. For the results of the subjective assessment, the experts argued that all images can be analyzed well.