NDLI: Segmentation-based image compression using BTC-VQ technique

Content Provider	IEEE Xplore Digital Library
Author	Kanafani, Q. Beghdadi, A. Fookes, C.
Copyright Year	2003
Description	Author affiliation: Univ. Paris, Villetaneuse, France (Kanafani, Q.; Beghdadi, A.)
Abstract	This paper proposes a new approach to image compression based on image segmentation using the EM algorithm and combined with BTC (block truncation coding) and VQ (vector quantization). The main idea is to decompose the image into homogeneous and nonhomogeneous blocks and then compress them using BTC or VQ. This block classification is achieved using an image segmentation based on the EM (expectation-maximization) algorithm. The use of the EM algorithm results in a good robust segmentation with well behaved boundaries. The segmented image is then used to specify whether BTC or VQ is used to encode a block by assessing if it contains all pixels from a homogeneous or nonhomogeneous region. BTC provides a simple and effective method for coding blocks which contain a lot of information or distinct edges due to its two-level quantizer. However, its lowest attainable bit rate is limited and it often introduces blocking effect in homogeneous regions. VQ on the other hand is more efficient due to a multilevel quantizer and thus results in better compression ratios. However, it does not retain any spatial information about the edges, resulting in stair casing effects. Previous attempts to combine both techniques into a hybrid algorithm only make use of simple measures such as image variance. Results for medical images show that this approach yields significant improvements over traditional BTC or VQ coding when used alone.
Starting Page	113
Ending Page	116
File Size	283817
Page Count	4
File Format	PDF
ISBN	0780379462
DOI	10.1109/ISSPA.2003.1224653
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-07-04
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Image coding Vector quantization Image storage Robustness Pixel Biomedical imaging Degradation Compression algorithms Signal processing
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
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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