Ultrafast and Efficient Scalable Image Compression Algorithm
<p>Wavelet-based image compression algorithms have good performance and produce a rate scalable bitstream that can be decoded efficiently at several bit rates. Unfortunately, the discrete wavelet transform (DWT) has relatively high computational complexity. On the other hand, the discrete cosi...
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doaj-5aafc17a5f8a4988817acfccb85d38f92020-11-24T23:08:31ZengITB Journal PublisherJournal of ICT Research and Applications2337-57872338-54992016-03-019321423510.5614/itbj.ict.res.appl.2015.9.3.21152Ultrafast and Efficient Scalable Image Compression AlgorithmAli Kadhim Jaber Al-Janabi0University of Kufa, Faculty of Engineering, Department of Electrical Engineering, Kufa Street, Najaf 21<p>Wavelet-based image compression algorithms have good performance and produce a rate scalable bitstream that can be decoded efficiently at several bit rates. Unfortunately, the discrete wavelet transform (DWT) has relatively high computational complexity. On the other hand, the discrete cosine transform (DCT) has low complexity and excellent compaction properties. Unfortunately, it is non-local, which necessitates implementing it as a block-based transform leading to the well-known blocking artifacts at the edges of the DCT blocks. This paper proposes a very fast and rate scalable algorithm that exploits the low complexity of DCT and the low complexity of the set partitioning technique used by the wavelet-based algorithms. Like JPEG, the proposed algorithm first transforms the image using block-based DCT. Then, it rearranges the DCT coefficients into a wavelet-like structure. Finally, the rearranged image is coded using a modified<em> </em>version of the SPECK algorithm, which is one of the best well-known wavelet-based algorithms. The modified SPECK consumes slightly less computer memory, has slightly lower complexity and slightly better performance than the original SPECK. The experimental results demonstrated that the proposed algorithm has competitive performance and high processing speed. Consequently, it has the best performance to complexity ratio among all the current rate scalable algorithms.</p>http://journals.itb.ac.id/index.php/jictra/article/view/1194 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ali Kadhim Jaber Al-Janabi |
spellingShingle |
Ali Kadhim Jaber Al-Janabi Ultrafast and Efficient Scalable Image Compression Algorithm Journal of ICT Research and Applications |
author_facet |
Ali Kadhim Jaber Al-Janabi |
author_sort |
Ali Kadhim Jaber Al-Janabi |
title |
Ultrafast and Efficient Scalable Image Compression Algorithm |
title_short |
Ultrafast and Efficient Scalable Image Compression Algorithm |
title_full |
Ultrafast and Efficient Scalable Image Compression Algorithm |
title_fullStr |
Ultrafast and Efficient Scalable Image Compression Algorithm |
title_full_unstemmed |
Ultrafast and Efficient Scalable Image Compression Algorithm |
title_sort |
ultrafast and efficient scalable image compression algorithm |
publisher |
ITB Journal Publisher |
series |
Journal of ICT Research and Applications |
issn |
2337-5787 2338-5499 |
publishDate |
2016-03-01 |
description |
<p>Wavelet-based image compression algorithms have good performance and produce a rate scalable bitstream that can be decoded efficiently at several bit rates. Unfortunately, the discrete wavelet transform (DWT) has relatively high computational complexity. On the other hand, the discrete cosine transform (DCT) has low complexity and excellent compaction properties. Unfortunately, it is non-local, which necessitates implementing it as a block-based transform leading to the well-known blocking artifacts at the edges of the DCT blocks. This paper proposes a very fast and rate scalable algorithm that exploits the low complexity of DCT and the low complexity of the set partitioning technique used by the wavelet-based algorithms. Like JPEG, the proposed algorithm first transforms the image using block-based DCT. Then, it rearranges the DCT coefficients into a wavelet-like structure. Finally, the rearranged image is coded using a modified<em> </em>version of the SPECK algorithm, which is one of the best well-known wavelet-based algorithms. The modified SPECK consumes slightly less computer memory, has slightly lower complexity and slightly better performance than the original SPECK. The experimental results demonstrated that the proposed algorithm has competitive performance and high processing speed. Consequently, it has the best performance to complexity ratio among all the current rate scalable algorithms.</p> |
url |
http://journals.itb.ac.id/index.php/jictra/article/view/1194 |
work_keys_str_mv |
AT alikadhimjaberaljanabi ultrafastandefficientscalableimagecompressionalgorithm |
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1716359772983263232 |