GERY - Faculty of Geography Repository
University of Belgrade - Faculty of Geography
    • English
    • Serbian (Cyrillic)
    • Serbian (Latin)
  • English 
    • English
    • Serbian (Cyrillic)
    • Serbian (Latin)
  • Login
View Item 
  •   GERY
  • Geografski fakultet
  • Radovi istraživača
  • View Item
  •   GERY
  • Geografski fakultet
  • Radovi istraživača
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Image data compression based on discrete wavelet transformation

No Thumbnail
Authors
Đoković, Marina
Peulić, Aleksandar
Jovanović, Željko
Damnjanović, Đorđe
Article (Published version)
Metadata
Show full item record
Abstract
Image compression research aims at reducing the number of bits needed to represent an image by removing the spatial and spectral redundancies as much as possible. New algorithms for image compression based on wavelets have been developed. These methods have resulted in practical advances such as: lossless and lossy compression, progressive transmission by pixel, accuracy and resolution, region of interest coding and others. The various wavelet based image coding schemes are discussed in this paper. Each of these schemes finds use in different applications owing to their unique characteristics. The methods of lossy compression that we concentrated on are the following: the EZW algorithm, the SPIHT algorithm, the WDR algorithm, and the ASWDR algorithm. These are relatively recent algorithms which achieve some of the lowest errors per compression rate and highest perceptual quality yet reported. After describing these algorithms in detail, we show and discuss the experimental results obta...ined for three different types of images. We also showed that some important features of image, such as standard deviation and mean pixel intensity values, only slightly change after compression. This fact is very important in medical image compression.

Keywords:
Discrete Wavelet Transformation / Image compression / Image coding schemes
Source:
Metalurgia International, 2012, 17, 9, 179-190
Publisher:
  • Editura Stiintifica Fmr, Bucharest

ISSN: 1582-2214

WoS: 000306248100032

[ Google Scholar ]
URI
https://gery.gef.bg.ac.rs/handle/123456789/461
Collections
  • Radovi istraživača
Institution/Community
Geografski fakultet
TY  - JOUR
AU  - Đoković, Marina
AU  - Peulić, Aleksandar
AU  - Jovanović, Željko
AU  - Damnjanović, Đorđe
PY  - 2012
UR  - https://gery.gef.bg.ac.rs/handle/123456789/461
AB  - Image compression research aims at reducing the number of bits needed to represent an image by removing the spatial and spectral redundancies as much as possible. New algorithms for image compression based on wavelets have been developed. These methods have resulted in practical advances such as: lossless and lossy compression, progressive transmission by pixel, accuracy and resolution, region of interest coding and others. The various wavelet based image coding schemes are discussed in this paper. Each of these schemes finds use in different applications owing to their unique characteristics. The methods of lossy compression that we concentrated on are the following: the EZW algorithm, the SPIHT algorithm, the WDR algorithm, and the ASWDR algorithm. These are relatively recent algorithms which achieve some of the lowest errors per compression rate and highest perceptual quality yet reported. After describing these algorithms in detail, we show and discuss the experimental results obtained for three different types of images. We also showed that some important features of image, such as standard deviation and mean pixel intensity values, only slightly change after compression. This fact is very important in medical image compression.
PB  - Editura Stiintifica Fmr, Bucharest
T2  - Metalurgia International
T1  - Image data compression based on discrete wavelet transformation
VL  - 17
IS  - 9
SP  - 179
EP  - 190
UR  - conv_1501
ER  - 
@article{
author = "Đoković, Marina and Peulić, Aleksandar and Jovanović, Željko and Damnjanović, Đorđe",
year = "2012",
abstract = "Image compression research aims at reducing the number of bits needed to represent an image by removing the spatial and spectral redundancies as much as possible. New algorithms for image compression based on wavelets have been developed. These methods have resulted in practical advances such as: lossless and lossy compression, progressive transmission by pixel, accuracy and resolution, region of interest coding and others. The various wavelet based image coding schemes are discussed in this paper. Each of these schemes finds use in different applications owing to their unique characteristics. The methods of lossy compression that we concentrated on are the following: the EZW algorithm, the SPIHT algorithm, the WDR algorithm, and the ASWDR algorithm. These are relatively recent algorithms which achieve some of the lowest errors per compression rate and highest perceptual quality yet reported. After describing these algorithms in detail, we show and discuss the experimental results obtained for three different types of images. We also showed that some important features of image, such as standard deviation and mean pixel intensity values, only slightly change after compression. This fact is very important in medical image compression.",
publisher = "Editura Stiintifica Fmr, Bucharest",
journal = "Metalurgia International",
title = "Image data compression based on discrete wavelet transformation",
volume = "17",
number = "9",
pages = "179-190",
url = "conv_1501"
}
Đoković, M., Peulić, A., Jovanović, Ž.,& Damnjanović, Đ.. (2012). Image data compression based on discrete wavelet transformation. in Metalurgia International
Editura Stiintifica Fmr, Bucharest., 17(9), 179-190.
conv_1501
Đoković M, Peulić A, Jovanović Ž, Damnjanović Đ. Image data compression based on discrete wavelet transformation. in Metalurgia International. 2012;17(9):179-190.
conv_1501 .
Đoković, Marina, Peulić, Aleksandar, Jovanović, Željko, Damnjanović, Đorđe, "Image data compression based on discrete wavelet transformation" in Metalurgia International, 17, no. 9 (2012):179-190,
conv_1501 .

DSpace software copyright © 2002-2015  DuraSpace
About GERY - GEography RepositoRY | Send Feedback

OpenAIRERCUB
 

 

All of DSpaceInstitutions/communitiesAuthorsTitlesSubjectsThis institutionAuthorsTitlesSubjects

Statistics

View Usage Statistics

DSpace software copyright © 2002-2015  DuraSpace
About GERY - GEography RepositoRY | Send Feedback

OpenAIRERCUB