RANCANG BANGUN APLIKASI KOMPRESI DAN DEKOMPRESI PADA CITRA DIGITAL MENGGUNAKAN METODE HUFFMAN

  • Kharisma Mahesa
  • Karpen .

Abstract

The rapid development of information technology and currently it’s possible to send information quickly. Speed transmission of information is certainly very dependent on the size of the capacity of such information. The large size of the capacity of information could result in the slow process of delivery. Beside that, the size of a large information capacity would require a very large storage space. The solution to this problem is to compress the information before sending in order to measure the capacity of such information becomes smaller. While reverting to forms the initial compression is to perform decompression technique. Some digital image compression techniques have been developed as block-coding, encoding and more. Digital image compression techniques continue to be developed with the aim to compress the image data as small as possible, but at the moment none of the decompression image data is lost. Huffman method is one method that is able to compress and decompress the digital image. Image compression is the process to minimize the number of bits that represents an image so that the image data capacity becomes smaller. Huffman method is a method of digital image compression is lossless compression method that is by doing the encoding in the form of bits to represent character data. Each type of characters contained in an image is calculated and sort by the fewest amount to a large amount in the form of binary trees and code for each character. The existing data will be replaced with the code bits based on a binary tree. Data that has been turned into a bit of code stored as a result of compression.

Published
2018-04-04
How to Cite
MAHESA, Kharisma; ., Karpen. RANCANG BANGUN APLIKASI KOMPRESI DAN DEKOMPRESI PADA CITRA DIGITAL MENGGUNAKAN METODE HUFFMAN. Jurnal MEDIA PROCESSOR, [S.l.], v. 12, n. 1, p. 948-963, apr. 2018. ISSN 2528-0082. Available at: <http://ejournal.stikom-db.ac.id/index.php/processor/article/view/367>. Date accessed: 17 july 2018.
Section
Articles

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