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Title:Stiskanje črno- belih slik z algoritmi delitve prostora : diplomsko delo
Authors:Lipuš, Satja (Author)
Lukač, Niko (Mentor) More about this mentor... New window
Files:.pdf UN_Lipus_Satja_2019.pdf (697,79 KB)
 
Language:Slovenian
Work type:Bachelor thesis/paper (mb11)
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:Stiskanje je proces zmanjševanja podatkov v pomnilniškem prostoru. V diplomskem delu predstavimo metodo stiskanja črno-belih slik z uporabo algoritmov, ki delijo prostor. Omejili smo se na sledeče tri metode deljenja prostora: enakomerna mreža, štiriško drevo in Kd drevo. Enakomerna mreža temelji na matematičnem modelu enakomerne kartezične mreže. Medtem, ko štiriško drevo rekurzivno deli prostor v štiri podprostore v obliki štiriškega podatkovnega drevesa, katerega vozlišča prestavljajo nadaljnjo delitev v globino. Kd drevo deli prostor v binarno drevo glede na mediano vrednosti, pri čemer vsako nadaljno rekuzijo izmenjuje dimenzijo delitve. Imenovani algoritmi predstavljajo obliko izgubnega stiskanja z različno učinkovitostjo. V diplomskem delu smo primerjali izgubo podatkov pri stiskanju poljubnih slik s predstavljenimi algoritmi in le to kvantitativno ocenili z uporabo metode povrečne kvadratne napake in strukturne podobnosti. Pri rezultatih smo ugotovili, da je pri delitvi prostora optimalna izbira štiriško drevo.
Keywords:stiskanje, razširjanje, črno-bele slike, delitev prostora, podatkovna drevesa.
Year of publishing:2019
Place of performance:Maribor
Publisher:[S. Lipuš]
Number of pages:V, 31 f.
Source:Maribor
UDC:004.932.021(043.2)
COBISS_ID:22927638 Link is opened in a new window
NUK URN:URN:SI:UM:DK:KFMMDX0S
License:CC BY-NC-ND 4.0
This work is available under this license: Creative Commons Attribution Non-Commercial No Derivatives 4.0 International
Views:52
Downloads:6
Metadata:XML RDF-CHPDL DC-XML DC-RDF
Categories:KTFMB - FERI
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Secondary language

Language:English
Title:Compression of binary images by using space partitioning algorithms
Abstract:Compression is a process of minimizing needed data to store given information on the computer. The thesis addresses one of the known methods of compression named space-division and applies it to a series of black and white images. We restricted ourselves to three space-division methods, namely Uniform Grid, Quad Tree and Kd Tree. Uniform Grid is based on the mathematical model of the Uniform Cartesian Grid. The method divides the space recursively into a uniform grid, independent of the values inside the space. Meanwhile the Quad Tree divides space in a form of a Quad Data Tree, where its nodes are further divisions while the leafs represent the final divided space. Kd Tree divides space based on the median of the spaces dimensions interchangeably, storing its data similarly to Quad Tree into a Binary Tree. The named algorithms represent a form of lossy compression with differing effectiveness. We compared their data loss compressing given images and described it with the structural similarity method. Looking at the results we concluded that that in regards to spacial division algorithm, the optimal choice is the quad tree.
Keywords:compression, decompression, monochromatic image, space-division, data trees.


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