Treffer: Lossless compression of VLSI layout image data

Title:
Lossless compression of VLSI layout image data
Authors:
DAI, Vito, ZAKHOR, Avideh
Source:
IEEE transactions on image processing. 15(9):2522-2530
Publisher Information:
New York, NY: Institute of Electrical and Electronics Engineers, 2006.
Publication Year:
2006
Physical Description:
print, 18 ref
Original Material:
INIST-CNRS
Subject Terms:
Telecommunications, Télécommunications, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Telecommunications et theorie de l'information, Telecommunications and information theory, Théorie de l'information, du signal et des communications, Information, signal and communications theory, Théorie du signal et des communications, Signal and communications theory, Codage, codes, Coding, codes, Traitement du signal, Signal processing, Traitement des images, Image processing, Circuit VLSI, VLSI circuit, Circuito VLSI, Circuit intégré, Integrated circuit, Circuito integrado, Codage binaire, Binary coding, Codificación binaria, Codage image, Image coding, Code Huffman, Huffman code, Código Huffman, Code arithmétique, Arithmetic code, Código aritmético, Code entropie, Entropy codes, Compression donnée, Data compression, Compresión dato, Compression image, Image compression, Compresión imagen, Compression sans perte, Lossless compression, Compresión sin pérdida, Evaluation performance, Performance evaluation, Evaluación prestación, Image binaire, Binary image, Imagen binaria, Lithographie, Lithography, Litografía, Modèle 2 dimensions, Two dimensional model, Modelo 2 dimensiones, Modélisation, Modeling, Modelización, Taux compression, Compression ratio, Relación compresión, Traitement image document, Document image processing, Traitement image, Image processing, Procesamiento imagen, Algorithme Lempel Ziv, Lempel Ziv algorithm, Context Copy Combinatorial Code (C4), compression, lithography, maskless
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Advanced Micro Devices, Sunnyvale, CA 94088-3453, United States
Video and Image Processing Lab, Department of Electrical Engineering and Computer Science, University of California, Berkeley 94720, United States
ISSN:
1057-7149
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=18049122
Rights:
Copyright 2006 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Telecommunications and information theory
Accession Number:
edscal.18049122
Database:
PASCAL Archive

Weitere Informationen

We present a novel lossless compression algorithm called Context Copy Combinatorial Code (C4), which integrates the advantages of two very disparate compression techniques: context-based modeling and Lempel-Ziv (LZ) style copying. While the algorithm can be applied to many lossless compression applications, such as document image compression, our primary target application has been lossless compression of integrated circuit layout image data. These images contain a heterogeneous mix of data: dense repetitive data better suited to LZ-style coding, and less dense structured data, better suited to context-based encoding. As part of C4, we have developed a novel binary entropy coding technique called combinatorial coding which is simultaneously as efficient as arithmetic coding, and as fast as Huffman coding. Compression results show C4 outperforms JBIG, ZIP, BZIP2, and two-dimensional LZ, and achieves lossless compression ratios greater than 22 for binary layout image data, and greater than 14 for gray-pixel image data.