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Abstract
In some kind of applications, such as in space image research, every detail of an image can be important. To send the information more efficiently over a network, the image will be compressed and in the former applications that must be done in a lossless manner. After decoding, a bit-equivalent version is obtained at the receiver. Therefore, the JPEG-LS standard can be used. However, this paper will introduce another approach for lossless image coding. At the encoder, we introduce a quantization error and which will be eliminated at the decoder by using an iterative procedure. The outcome of this procedure is an attractor (or fractal) which has to be the original image. We discuss different implementations of a fractal lossless encoder and come to the conclusion that we can achieve a compression that is comparable to JPEG-LS, but not better at the moment.
Keywords
JPEG-LS, lossless image coding, attractor coding, fractals

Citation

Please use this url to cite or link to this publication:

MLA
De Schrijver, Davy, Robbie De Sutter, Peter Lambert, et al. “Lossless Image Coding Based on Fractals.” Seventh Lasted International Conference on Signal and Image Processing. Ed. MW Marcellin. Calgary, AB, Canada: ACTA Press, 2005. 52–57. Print.
APA
De Schrijver, D., De Sutter, R., Lambert, P., & Van de Walle, R. (2005). Lossless image coding based on fractals. In M. Marcellin (Ed.), SEVENTH LASTED INTERNATIONAL CONFERENCE ON SIGNAL AND IMAGE PROCESSING (pp. 52–57). Presented at the 7th IASTED International Conference on Signal and Image Processing, Calgary, AB, Canada: ACTA Press.
Chicago author-date
De Schrijver, Davy, Robbie De Sutter, Peter Lambert, and Rik Van de Walle. 2005. “Lossless Image Coding Based on Fractals.” In Seventh Lasted International Conference on Signal and Image Processing, ed. MW Marcellin, 52–57. Calgary, AB, Canada: ACTA Press.
Chicago author-date (all authors)
De Schrijver, Davy, Robbie De Sutter, Peter Lambert, and Rik Van de Walle. 2005. “Lossless Image Coding Based on Fractals.” In Seventh Lasted International Conference on Signal and Image Processing, ed. MW Marcellin, 52–57. Calgary, AB, Canada: ACTA Press.
Vancouver
1.
De Schrijver D, De Sutter R, Lambert P, Van de Walle R. Lossless image coding based on fractals. In: Marcellin M, editor. SEVENTH LASTED INTERNATIONAL CONFERENCE ON SIGNAL AND IMAGE PROCESSING. Calgary, AB, Canada: ACTA Press; 2005. p. 52–7.
IEEE
[1]
D. De Schrijver, R. De Sutter, P. Lambert, and R. Van de Walle, “Lossless image coding based on fractals,” in SEVENTH LASTED INTERNATIONAL CONFERENCE ON SIGNAL AND IMAGE PROCESSING, Honolulu, HI, USA, 2005, pp. 52–57.
@inproceedings{405616,
  abstract     = {In some kind of applications, such as in space image research, every detail of an image can be important. To send the information more efficiently over a network, the image will be compressed and in the former applications that must be done in a lossless manner. After decoding, a bit-equivalent version is obtained at the receiver. Therefore, the JPEG-LS standard can be used. However, this paper will introduce another approach for lossless image coding. At the encoder, we introduce a quantization error and which will be eliminated at the decoder by using an iterative procedure. The outcome of this procedure is an attractor (or fractal) which has to be the original image. We discuss different implementations of a fractal lossless encoder and come to the conclusion that we can achieve a compression that is comparable to JPEG-LS, but not better at the moment.},
  author       = {De Schrijver, Davy and De Sutter, Robbie and Lambert, Peter and Van de Walle, Rik},
  booktitle    = {SEVENTH LASTED INTERNATIONAL CONFERENCE ON SIGNAL AND IMAGE PROCESSING},
  editor       = {Marcellin, MW},
  isbn         = {0-88986-516-7},
  keywords     = {JPEG-LS,lossless image coding,attractor coding,fractals},
  language     = {eng},
  location     = {Honolulu, HI, USA},
  pages        = {52--57},
  publisher    = {ACTA Press},
  title        = {Lossless image coding based on fractals},
  year         = {2005},
}

Web of Science
Times cited: