DocumentCode :
1548402
Title :
Two low cost algorithms for improved diagonal edge detection in JPEG-LS
Author :
Grecos, C. ; Jiang, J. ; Edirisinghe, E.A.
Author_Institution :
Sch. of Comput., Glamorgan Univ., Pontypridd, UK
Volume :
47
Issue :
3
fYear :
2001
fDate :
8/1/2001 12:00:00 AM
Firstpage :
466
Lastpage :
473
Abstract :
JPEG-LS is the latest lossless and near lossless image compression standard introduced by the Joint Photographic Experts Group (JPEG) in 1999. In this standard simple localized edge detection techniques are used in order to determine the predictive value of each pixel. These edge detection techniques only detect horizontal and vertical edges and the corresponding predictors have only been optimized for the accurate prediction of pixels in the locality of horizontal and/or vertical edges. As a result JPEG-LS produces large prediction errors in the locality of diagonal edges. We present two low cost algorithms for the detection and prediction of diagonal edge pixels in JPEG-LS. Experimental results show that the proposed schemes aid in the reduction of predictive mean squared error of up to 2-3 percent as compared to the standard
Keywords :
code standards; data compression; edge detection; image coding; mean square error methods; prediction theory; telecommunication standards; JPEG; JPEG-LS; Joint Photographic Experts Group; MSE reduction; diagonal edge detection; diagonal edge pixels detection; diagonal edge pixels prediction; image compression; localized edge detection; lossless image compression standard; low cost algorithms; mean squared error; near lossless image compression standard; pixel predictive value; prediction errors; Computational efficiency; Computer science; Consumer electronics; Costs; Digital images; Digital photography; Image coding; Image edge detection; Standards development; Transform coding;
fLanguage :
English
Journal_Title :
Consumer Electronics, IEEE Transactions on
Publisher :
ieee
ISSN :
0098-3063
Type :
jour
DOI :
10.1109/30.964135
Filename :
964135
Link To Document :
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