This paper present three characteristic functions which can express the luminance distribute characteristic much better. Based on these functions a region classification algorithm is presented. The algorithm can offer more information on regions' similarity and greatly improve the efficiency and performance of match seeking in fractal coding. It can be widely applied to many kinds of fractal coding algorithms. Analysis and experimental results proved that it can offer more information on luminance distribute characteristics among regions and greatly improve the decoding quality and compression ratio with holding the running speed.
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Copy
ChenGuang ZHOU, Kui MENG, ZuLian QIU, "A Classification Algorithm Based on Regions' Luminance Distribution Applying to Fractal Image Compression" in IEICE TRANSACTIONS on Information,
vol. E88-D, no. 9, pp. 2223-2227, September 2005, doi: 10.1093/ietisy/e88-d.9.2223.
Abstract: This paper present three characteristic functions which can express the luminance distribute characteristic much better. Based on these functions a region classification algorithm is presented. The algorithm can offer more information on regions' similarity and greatly improve the efficiency and performance of match seeking in fractal coding. It can be widely applied to many kinds of fractal coding algorithms. Analysis and experimental results proved that it can offer more information on luminance distribute characteristics among regions and greatly improve the decoding quality and compression ratio with holding the running speed.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e88-d.9.2223/_p
Copy
@ARTICLE{e88-d_9_2223,
author={ChenGuang ZHOU, Kui MENG, ZuLian QIU, },
journal={IEICE TRANSACTIONS on Information},
title={A Classification Algorithm Based on Regions' Luminance Distribution Applying to Fractal Image Compression},
year={2005},
volume={E88-D},
number={9},
pages={2223-2227},
abstract={This paper present three characteristic functions which can express the luminance distribute characteristic much better. Based on these functions a region classification algorithm is presented. The algorithm can offer more information on regions' similarity and greatly improve the efficiency and performance of match seeking in fractal coding. It can be widely applied to many kinds of fractal coding algorithms. Analysis and experimental results proved that it can offer more information on luminance distribute characteristics among regions and greatly improve the decoding quality and compression ratio with holding the running speed.},
keywords={},
doi={10.1093/ietisy/e88-d.9.2223},
ISSN={},
month={September},}
Copy
TY - JOUR
TI - A Classification Algorithm Based on Regions' Luminance Distribution Applying to Fractal Image Compression
T2 - IEICE TRANSACTIONS on Information
SP - 2223
EP - 2227
AU - ChenGuang ZHOU
AU - Kui MENG
AU - ZuLian QIU
PY - 2005
DO - 10.1093/ietisy/e88-d.9.2223
JO - IEICE TRANSACTIONS on Information
SN -
VL - E88-D
IS - 9
JA - IEICE TRANSACTIONS on Information
Y1 - September 2005
AB - This paper present three characteristic functions which can express the luminance distribute characteristic much better. Based on these functions a region classification algorithm is presented. The algorithm can offer more information on regions' similarity and greatly improve the efficiency and performance of match seeking in fractal coding. It can be widely applied to many kinds of fractal coding algorithms. Analysis and experimental results proved that it can offer more information on luminance distribute characteristics among regions and greatly improve the decoding quality and compression ratio with holding the running speed.
ER -