Algoritmi sažimanja bez gubitaka

master's thesis

• Title (english): Lossless compression algorithms
• Author: Matea Pešut
• Mentor: Goranka Nogo (mentor)
• Committee member: Goranka Nogo (predsjednik povjerenstva)
• Committee member: Marcela Hanzer (član povjerenstva)
• Committee member: Željka Milin Šipuš (član povjerenstva)
• Committee member: Mea Bombardelli (član povjerenstva)
• Granter: University of Zagreb; Faculty of Science; (Department of Mathematics); Zagreb
• Defense date and country: 2023-09-29, Croatia
• Scientific / art field, discipline and subdiscipline: NATURAL SCIENCES; Mathematics

Abstract

U današnjem digitalnom svijetu, brza i efikasna kompresija podataka od iznimne je važnosti za učinkovitu pohranu, prijenos i obradu informacija. Ovaj radi fokusira se na algoritme sažimanja bez gubitaka koji u potpunosti mogu obnoviti ulazne podatke nakon kodiranja. Opisano je nekoliko algoritama koji pripadaju trima tehnikama kompresije, Variable-Length, statističkom i univerzalnom kodiranju i uspoređene su performanse odabranih algoritama na nekoliko skupova podataka. Rezultati su pokazali da ne postoji univerzalno najbolji algoritam sažimanja. Umjesto toga, izbor algoritma ovisi o specifičnim potrebama aplikacije. Ukoliko je najvažnija mala veličina kodiranog podatka i brzina nije od presudne važnosti, aritmetičko kodiranje odličan je izbor. Međutim, za brze aplikacije koje zahtijevaju dobru kompresiju LZW i Huffmanov algoritam pružaju razumne rezultate. Ovaj rad naglašava važnost razumijevanja različitih algoritama sažimanja podataka i njihovih performansi kako bi se odabrao najprikladniji za određenu situaciju.

Abstract (english)

In today’s digital world, fast and efficient data compression is of utmost importance for efficient storage, transmission, and processing of information. This paper focuses on lossless compression algorithms that can fully restore input data after encoding. Several algorithms belonging to three compression techniques, Variable-Length, Statistical, and Universal coding, are described, and the performance of selected algorithms on multiple datasets is compared. The results have shown that there is no universally best compression algorithm. Instead, the choice of algorithm depends on the specific needs of the application. If achieving a small encoded data size is crucial, and speed is not of topmost importance, Arithmetic coding is an excellent choice. However, for fast applications requiring good compression, LZW and Huffman coding provide reasonable results. This paper emphasizes the importance of understanding different data compression algorithms and their performance to select the most suitable one for a specific situation.

• Keywords: kompresija podataka; pohrana; prijenos i obrada informacija; Huffmanov algoritam
• Keywords (english): data compression; efficient storage; transmission; and processing of information; Huffman coding
• Language: croatian
• URN:NBN: urn:nbn:hr:217:583805
• Study programme: Title: Computer Science and Mathematics; Study programme type: university; Study level: graduate; Academic / professional title: sveučilišni magistar računarstva i matematike (sveučilišni magistar računarstva i matematike)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2024-02-05 12:50:57