Brezizgubno stiskanje rastrskih slik z uporabo genetskega algoritma

magistrsko delo

Tomaž Klobučar (Author), David Jesenko (Mentor), Marko Bizjak (Co-mentor)

Abstract

V magistrskem delu je predstavljena uporaba genetskega algoritma za brezizgubno stiskanje rastrskih slik. Poudarek je na kombiniranju genetskega algoritma z različnimi tehnikami stiskanja podatkov, vključno z aritmetičnim kodiranjem, metodo RLE (angl. Run Length Encoding) in Huffmanovim kodiranjem. Podrobno je opisano teoretično ozadje genetskega algoritma in njegovih osnovnih postopkov, kot so selekcija, križanje in mutacija. Prav tako je predstavljena implementacija genetskega algoritma, kodirnika in dekodirnika. Opravljene so bile analize vhodnih parametrov kodeka, stiskanja splošnih in risanih slik, vpliva napovedi genetskega algoritma na stopnjo stiskanja, vpliva pretvorbe barvnega prostora na stopnjo stiskanja ter analiza časovne zahtevnosti. Rezultati so pokazali, da predlagan kodek doseže stopnjo stiskanja primerljivo z izbranimi formati, njegova učinkovitost stiskanja pa se izboljša z uporabo pretvorbe barvnega prostora.

Keywords

brezizgubno stiskanje slik;risane slike;genetski algoritem;Huffmanovo kodiranje;aritmetično kodiranje;magistrske naloge;

Data

Language:	Slovenian
Year of publishing:	2025
Typology:	2.09 - Master's Thesis
Organization:	UM FERI - Faculty of Electrical Engineering and Computer Science
Publisher:	[T. Klobučar]
UDC:	004.627:004.932(043.2)
COBISS:	226810371
Views:	0
Downloads:	6
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	Lossless raster image compression using genetic algorithm
Secondary abstract:	The thesis explores the application of a genetic algorithm for lossless compression of raster images. It focuses on integrating the genetic algorithm with various data compression techniques, including arithmetic coding, RLE (Run Length Encoding), and Huffman coding. The theoretical foundations of the genetic algorithm are discussed in detail, covering key processes such as selection, crossover, and mutation. Additionally, the implementation of a genetic algorithm, encoder, and decoder is presented. Analyses were conducted on the codec's input parameters, the compression of general and cartoon images, the impact of the genetic algorithm's prediction on compression rates, the impact of color space conversion on compression rates, and the algorithm's time complexity. The results demonstrate that the proposed codec achieves a compression rate comparable to selected formats, with its efficiency further improving when color space conversion is applied.
Secondary keywords:	lossless image compression;cartoon images;genetic algorithm;Huffman coding;arithmetic coding;RLE;
Type (COBISS):	Master's thesis/paper
Thesis comment:	Univ. v Mariboru, Fak. za elektrotehniko, računalništvo in informatiko, Računalništvo in informacijske tehnologije
Pages:	1 spletni vir (1 datoteka PDF (X, 45 str.))
ID:	25750490