Czasopismo
2009
|
Vol. 91, nr 3-4
|
533-546
Tytuł artykułu
Autorzy
Wybrane pełne teksty z tego czasopisma
Warianty tytułu
Języki publikacji
Abstrakty
Hypergraphs are a large generalisation of graphs; they are now used for many low-level image processing, by example for noise reduction, edge detection and segmentation [3, 4, 7]. In this paper we define a generic 2D and 3D-image representation based on a hypergraph. We present the mathematical definition of the hypergraph representation of an image and we show how this representation conducts to an efficient lossless compression algorithm for 2D and 3D-images. Then we introduce both 2D and 3D version of the algorithm and we give some experimental results on some various sets of images: 2D photo, 2D synthetic pictures, 3D medical images and some short animated sequences.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
533-546
Opis fizyczny
Bibliogr. 18 poz., tab., wykr.
Twórcy
autor
autor
- Université de Caen, GREYC UMR-6072 Campus II, Bd Marechal Juin BP 5186, 14032 Caen cedex, France, luc.gillibert@info.unicaen.fr
Bibliografia
- [1] C. HEBERT, A. BRETTO and B. CREMILLEUX. A data mining formalization to improve hypergraph minimal transversal computation, Fundamenta Informaticae Vol. 79, 2007, pages 1-19.
- [2] A. BRETTO. Introduction to Hypergraph Theory and Its Use in Engineering and Image Processing. Monography in Advances in Imaging and Electron Physics. Academic Press Elsevier, Vol. 131, march 2004.
- [3] A. BRETTO, J. AZEMA, H. CHERIFI, and B. LAGET. Combinatoric and image processing. Computer Vision, Graphic and Image Processing (Graphical Model and Image Processing), 59(5), Septembre 1997, pages 128-132.
- [4] A. BRETTO and and L. GILLIBERT. Hypergraph-Based Image Representation. Graph-Based Representations in Pattern Recognition (GbRPR 2005), Poitiers, April 11-13. Lecture Notes in Computer Science 3434, Springer-Verlag 2005, pages 1-11.
- [5] A. BRETTO and L. GILLIBERT. Hypergraph Lossless Image Compression. International Conference on Information Technology (ITCC 2005), Las Vegas, April 4-6. IEEE Computer Society 2005, Vol. 1, pages 46-50.
- [6] L. GILLIBERT and A. BRETTO. Hypergraphs for Near-lossless Volumetric Compression. ITNG 2007. IEEE Computer Society 2007, Vol. 1, pages 229-233.
- [7] A. BRETTO, H. CHERIFI, and D. ABOUTAJDINE. Hypergraph imaging: an overview. Pattern Recognition, 35(3), 2001, pages 651-658.
- [8] L. CIEPLINSKI. A Review of Image and Video Coding Standards, Fundamenta Informaticae Vol. 34, 1998, pages 347-367.
- [9] Yung-Kuan CHAN, Her-Fa WANG and Chin-Fan LEE. A Refined VQ-Based Image Compression Method. Fundamenta Informaticae Vol. 61, 2004, pages 313-321.
- [10] Wojciech JAWORSKI. An Improved Tree-Structured Codebook Search Algorithm for Grayscale Image Compression. Fundamenta Informaticae Vol. 70, 2006, pages 251-260.
- [11] M. WEINBERGER, G. SEROUSSI and G. SAPIRO. The LOCO-I Lossless Image Compression Algorithm: Principles and Standardisation into JPEG-LS. Hewlett-Packard Laboratories Technical Report No. HPL-98-193R1, November 1998, revised October 1999. IEEE Trans. Image Processing, Vol. 9, August 2000, pages 1309-1324.
- [12] C. BERGE. Hypergraphs. North-Holland Mathematical Library, 1989.
- [13] PNG Development Group, Portable Network Graphics Specification v1.2. URL: www.libpng.org/pub/png/spec/1.2/
- [14] Fnord SuperPNG Advanced PNG plug-in. URL: http://www.fnordware.com/superpng/
- [15] Dmitry SHKARIN. PPM: one step to practicality, Data Compression Conference (DCC '02), IEEE Computer Society, 2002. URL for the program: http://compression.ru/ds/ppmdi1.rar
- [16] John G. CLEARY, W. J. TEAHUN, Ian H. WITTEN. Unbounded Length Contexts for PPM. The Computer Journal, 1995.
- [17] C.A. COCOSCO, V. KOLLOKIAN, R.K.-S. KWAN, A.C. EVANS. BrainWeb: Online Interface to a 3D MRI Simulated Brain Database, NeuroImage, vol.5, no.4, part 2/4, S425, 1997 - Proceedings of 3-rd International Conference on Functional Mapping of the Human Brain, Copenhagen, May 1997. URL: http://www.bic.mni.mcgill.ca/brainweb/
- [18] Allan WEBER. The USC-SIPI Image Database. Signal and Image Processing Institute of the University of Southern California. URL: http://sipi.usc.edu/services/database/
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.baztech-article-BUS8-0004-0054