Implementasi dan Analisis Kinerja Algoritma Arithmetic Coding dan Shannon-Fano pada Kompresi Citra BMP

Abstract

Rapid technological developments, a very important role in the rapid exchange of information. On the transmission of information in the form of the image is still experiencing problems, such as the large size of the image so that the solution to that problem is to do the compression. In this thesis will implement and compare the performance of the algorithm Arithmetic Coding and Shannon-Fano through the calculation of compression ratio, the size of the compressed file, the speed of compression and decompression process. Based on all the test results, that Arithmetic Coding algorithm yielded an average compression ratio of 62.88% and a compression ratio Shannon-Fano of 61.73%, Arithmetic Coding the average speed in image compression is 0.072449 seconds and Shannon-Fano 0,077838 seconds. Then the Shannon-Fano algorithm has an average speed for the decompression algorithm is 0.028946 second and Arithmetic Coding 0.034169 seconds. Image decompression algorithm results Arithmetic Coding and Shannon-Fano line with the original image. Can be concluded from the results of testing that Arithmetic Coding algorithm is more efficient in image compression *.bmp than Shannon-Fano algorithm, although in terms of Shannon-Fano decompress a bit faster than Arithmetic Coding.