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Content Provider | IEEE Xplore Digital Library |
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Author | Boncelet, C. |
Copyright Year | 2006 |
Description | Author affiliation: Dept. of Electr. & Comput. Eng., Delaware Univ., Newark, DE, USA (Boncelet, C.) |
Abstract | We present a new lossless image compression algorithm called BCTW, for bitplane context tree weighting, and a corresponding study into lossless image compression using several number representations and various algorithms. BCTW processes the image bitplane by bitplane and uses context tree weighting (CTW) to estimate the probability of each pixel bit being a 1 or 0. The bit is then compressed with an entropy coder, most likely an arithmetic coder. BCTW is a very good lossless image compressor. In the study, we also look at several number representations (twos-complement, Gray coding, and sign-magnitude) and compare BCTW to MedBzip2 and JPEG-LS. On the Waterloo Bragzone GreySet2 dataset, BCTW outperforms JPEG-LS by 13% and MedBzip2 by 5%. We find that representing the pixels in a Gray code does not help. Sign-magnitude helps sometimes, but not in BCTW. The MED transform helps bzip2, but not BCTW. |
Starting Page | 2281 |
Ending Page | 2284 |
File Size | 4199643 |
Page Count | 4 |
File Format | |
ISBN | 1424404800 |
ISSN | 15224880 |
DOI | 10.1109/ICIP.2006.312818 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2006-10-08 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Image coding Entropy Image edge detection Pixel Testing Arithmetic Reflective binary codes Detectors Information theory Cryptography |
Content Type | Text |
Resource Type | Article |
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