Image data compression based on discrete wavelet transformation
Апстракт
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.
Кључне речи:
Discrete Wavelet Transformation / Image compression / Image coding schemesИзвор:
Metalurgia International, 2012, 17, 9, 179-190Издавач:
- Editura Stiintifica Fmr, Bucharest
Колекције
Институција/група
Geografski fakultetTY - 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 - https://hdl.handle.net/21.15107/rcub_gery_461 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 = "https://hdl.handle.net/21.15107/rcub_gery_461" }
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. https://hdl.handle.net/21.15107/rcub_gery_461
Đoković M, Peulić A, Jovanović Ž, Damnjanović Đ. Image data compression based on discrete wavelet transformation. in Metalurgia International. 2012;17(9):179-190. https://hdl.handle.net/21.15107/rcub_gery_461 .
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, https://hdl.handle.net/21.15107/rcub_gery_461 .