NDLI: Enhanced embedded zerotree wavelet algorithm for lossy image coding

Content Provider	IET Digital Library
Author	Boujelbene, Rania Boubchir, Larbi Jemaa, Yousra Ben
Abstract	Embedded zerotree wavelet (EZW) algorithm is the well-known effective coding technique for low-bit-rate image compression. In this study, the authors propose a modification of this algorithm, namely new enhanced EZW (NE-EZW), allowing to achieve a high compression performance in terms of peak-signal-to-noise ratio and bitrate for lossy image compression. To distribute probabilities in a more efficient way, the proposed approach is based on increasing the number of coefficients not to be encoded by the use of new symbols. Furthermore, the proposed method optimises the binary coding by the use of the compressor cell operator. Experimental results demonstrated the effectiveness of the proposed scheme over the conventional EZW and other improved EZW schemes for both natural and medical image coding applications. They have also shown that the proposed approach outperforms the most well-known algorithms, namely set partitioning in hierarchical trees (SPIHT) and JPEG2000.
Starting Page	1364
Ending Page	1374
Page Count	11
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 8, Jun (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.6052
Journal	IET Image Processing
Publisher Date	2019-04-26
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Binary Codes Binary Coding Code Combinatorial Mathematics Computer Vision And Image Processing Technique Conventional EZW Data Compression Effective Coding Technique Embedded Zerotree Wavelet Algorithm Enhanced EZW Hierarchical Trees High Compression Performance Image And Video Coding Image Coding Improved EZW Scheme Integral Transforms JPEG2000 Lossy Image Coding Lossy Image Compression Low-bit-rate Image Compression Mathematics Medical Image Coding Application Natural Image Coding Application Peak-signal-to-noise Ratio SPIHT Trees Wavelet Transform
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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