A lossless image compression technique using generic peano pattern mask tree

Mohammad Kabir Hossain; Shams M. Imam; Khondker Shajadul Hasan; William Perrizo

doi:10.1109/ICCITECHN.2008.4802980

A lossless image compression technique using generic peano pattern mask tree

Mohammad Kabir Hossain, Shams M. Imam, Khondker Shajadul Hasan, William Perrizo

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

Digital Image processing has become ubiquitous in our daily life and the demands to produce and process images are ever increasing. Large amounts of space are required to store these images. Image compression techniques are in high demand as they allow reduction in this storage space. The basis for image compression, as is for most other compression techniques, is to remove redundant and unimportant data. Lossless image compression techniques retain the original information in compact form and do not introduce any errors when decompressed. In this paper, we discuss such a lossless technique using a data structure that we name "Generic Peano Pattern Mask Tree". It is an improvement over a previously discussed Lossless Image compression technique - "Peano Pattern Mask Tree". Both these structures are based on the data structure - Peano Mask Tree.

Original language	English (US)
Title of host publication	Proceedings of 11th International Conference on Computer and Information Technology, ICCIT 2008
Pages	317-322
Number of pages	6
DOIs	https://doi.org/10.1109/ICCITECHN.2008.4802980
State	Published - 2008
Externally published	Yes
Event	11th International Conference on Computer and Information Technology, ICCIT 2008 - Khulna, Bangladesh Duration: Dec 25 2008 → Dec 27 2008

Publication series

Name	Proceedings of 11th International Conference on Computer and Information Technology, ICCIT 2008

Conference

Conference	11th International Conference on Computer and Information Technology, ICCIT 2008
Country/Territory	Bangladesh
City	Khulna
Period	12/25/08 → 12/27/08

Keywords

Data mining Ready
Generic Peano Pattern Mask Tree
Lossless Image Compression
Peano Mask Tree
Peano Pattern Mask Tree
Peano Tree

Access

10.1109/ICCITECHN.2008.4802980

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Cite this

Hossain, M. K., Imam, S. M., Hasan, K. S., & Perrizo, W. (2008). A lossless image compression technique using generic peano pattern mask tree. In Proceedings of 11th International Conference on Computer and Information Technology, ICCIT 2008 (pp. 317-322). Article 4802980 (Proceedings of 11th International Conference on Computer and Information Technology, ICCIT 2008). https://doi.org/10.1109/ICCITECHN.2008.4802980

A lossless image compression technique using generic peano pattern mask tree. / Hossain, Mohammad Kabir; Imam, Shams M.; Hasan, Khondker Shajadul et al.
Proceedings of 11th International Conference on Computer and Information Technology, ICCIT 2008. 2008. p. 317-322 4802980 (Proceedings of 11th International Conference on Computer and Information Technology, ICCIT 2008).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Hossain, MK, Imam, SM, Hasan, KS & Perrizo, W 2008, A lossless image compression technique using generic peano pattern mask tree. in Proceedings of 11th International Conference on Computer and Information Technology, ICCIT 2008., 4802980, Proceedings of 11th International Conference on Computer and Information Technology, ICCIT 2008, pp. 317-322, 11th International Conference on Computer and Information Technology, ICCIT 2008, Khulna, Bangladesh, 12/25/08. https://doi.org/10.1109/ICCITECHN.2008.4802980

Hossain MK, Imam SM, Hasan KS, Perrizo W. A lossless image compression technique using generic peano pattern mask tree. In Proceedings of 11th International Conference on Computer and Information Technology, ICCIT 2008. 2008. p. 317-322. 4802980. (Proceedings of 11th International Conference on Computer and Information Technology, ICCIT 2008). doi: 10.1109/ICCITECHN.2008.4802980

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A lossless image compression technique using generic peano pattern mask tree

Abstract

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Keywords

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