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Title:
Spremenjena diskretna kosinusna transformacija s psihoakustičnim modelom za stiskanje zvoka
Authors:
ID
Premoša, Grega
(
Author
)
ID
Lukač, Niko
(
Mentor
)
More about this mentor...
Files:
UN_Premosa_Grega_2018.pdf
(1,01 MB)
MD5: 315FE2947BDE63DA8B7366DAE78D55C0
PID:
20.500.12556/dkum/b858e081-1c71-4a74-8a10-253f01861f6c
Language:
Slovenian
Work type:
Bachelor thesis/paper
Typology:
2.11 - Undergraduate Thesis
Organization:
FERI - Faculty of Electrical Engineering and Computer Science
Abstract:
V diplomskem delu predstavimo metodo za izgubno stiskanje zvoka z uporabo psihoakustičnega modela in algoritma spremenjene diskretne kosinusne transformacije. Podatke prenesemo v frekvenčno domeno in odstranimo odseke, katerih človek ni sposoben zaznati. S kosinusno transformacijo pretvorimo podatke naraščujoče po frekvenci in porežemo visoko frekvenčno vsebino. V zadnji fazi uporabimo stiskanje z Lempel-Ziv algoritmom na podlagi markovske verige (LZMA). V rezultatih smo izvedli analizo občutljivosti glede na različne vrednosti vhodnih parametrov metode ter analizo uspešnosti stiskanja glede na kvaliteto izhoda.
Keywords:
Stiskanje zvoka
,
psihoakustični model
,
spremenjena diskretna kosinusna transformacija
,
frekvenčna analiza
,
LZMA.
Place of publishing:
[Maribor
Publisher:
G. Premoša
Year of publishing:
2018
PID:
20.500.12556/DKUM-71117
UDC:
004.9:512.817(043.2)
COBISS.SI-ID:
21745686
NUK URN:
URN:SI:UM:DK:FIZIHYR2
Publication date in DKUM:
28.08.2018
Views:
1659
Downloads:
166
Metadata:
Categories:
KTFMB - FERI
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Licences
License:
CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:
http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:
The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:
15.07.2018
Secondary language
Language:
English
Title:
Sound compression by using modified discrete cosine transform and psychoacoustic model
Abstract:
In our thesis, we present a sound compression algorithm using modified discrete cosine transformation and psychoacoustic model. Original data is transformed into frequency domain, where inaudible parts of the human ear are removed. With modified discrete cosine transform the data is transformed into an ascending list of their frequency content, after which high frequencies are cut for better compression. Final part of the algorithm uses lossless Lempel–Ziv–Markov chain algorithm (LZMA). Implemented algorithm was parameterized and sensitivity analysis was performed on sound quality.
Keywords:
Sound compression
,
psychoacoustic model
,
modified discrete cosine transform
,
frequency analysis
,
LZMA.
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