TY - CHAP

T1 - Lossless Coding

AU - Karam, Lina

N1 - Funding Information:
The JBIG (Joint Binary Image Experts Group) standard (ITU-T Recommendation T.82, 1993) was developed jointly by the ITU and the ISO/IEC with the objective to provide improved lossless compression performance, for both business-type documents and binary halftone images, as compared to the existing standards. Another objective was to support progressive transmission. Gray scale images are also supported by encoding separately each bit-plane. Later, the same JBIG committee drafted the IBIG2 standard (ITU-T Recommendation T.88, 2000) which provides improved lossless compression as compared to JBIG in addition to allowing lossy compression of bi-level images.
Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.

PY - 2005

Y1 - 2005

N2 - The goal of lossless image compression is to represent an image signal with the smallest possible number of bits without a loss of any information, thereby speeding up transmission and minimizing storage requirements. This chapter introduces the basics of lossless image coding and presents classical as well as some more recently developed lossless compression methods. Lossless symbol coding is commonly referred to as "lossless coding" or "lossless compression." The popular lossless symbol coding schemes fall into one of the following main categories: statistical schemes (Huffman, Arithmetic) and dictionary-based schemes (Lempel-Ziv). Statistical schemes require the knowledge of the source symbol probability distribution. Dictionary-based schemes do not require a priori knowledge of the source symbol probability distribution. They dynamically construct encoding and decoding tables of variable-length symbol strings as and when they occur in the input data. The operations of a lossless image encoder can be grouped into three stages: transformation, data to symbol mapping, and lossless symbol coding. The factors that need to be considered when choosing or devising a lossless compression scheme are compression efficiency, coding delay, implementation complexity, robustness, and scalability.

AB - The goal of lossless image compression is to represent an image signal with the smallest possible number of bits without a loss of any information, thereby speeding up transmission and minimizing storage requirements. This chapter introduces the basics of lossless image coding and presents classical as well as some more recently developed lossless compression methods. Lossless symbol coding is commonly referred to as "lossless coding" or "lossless compression." The popular lossless symbol coding schemes fall into one of the following main categories: statistical schemes (Huffman, Arithmetic) and dictionary-based schemes (Lempel-Ziv). Statistical schemes require the knowledge of the source symbol probability distribution. Dictionary-based schemes do not require a priori knowledge of the source symbol probability distribution. They dynamically construct encoding and decoding tables of variable-length symbol strings as and when they occur in the input data. The operations of a lossless image encoder can be grouped into three stages: transformation, data to symbol mapping, and lossless symbol coding. The factors that need to be considered when choosing or devising a lossless compression scheme are compression efficiency, coding delay, implementation complexity, robustness, and scalability.

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U2 - 10.1016/B978-012119792-6/50101-7

DO - 10.1016/B978-012119792-6/50101-7

M3 - Chapter

AN - SCOPUS:84882909557

SN - 9780121197926

SP - 643

EP - 660

BT - Handbook of Image and Video Processing

PB - Elsevier Inc.

ER -