.png){kind=icon}
.png){kind=icon}
Return
Why does histogram packing improve lossless compression rates?
.png){kind=icon}
PRE
AI
DOI：10.1109/LSP.2002.803018.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The performance of state-of-the-art lossless image coding methods [such as JPEG-LS, lossless JPEG-2600, and context-based adaptive lossless image coding (CALIC)] can be considerably improved by a recently introduced preprocessing technique that can be applied whenever the images have sparse histograms. Bitrate savings of up to 50% have been reported, but so far no theoretical explanation of the fact has been advanced. This letter addresses this issue and analyzes the effect of the technique in terms of the interplay between histogram packing and the image total variation, emphasizing the lossless JPEG-2000 case.
Keywords:
context-based adaptive lossless image coding
(CALIC)
histogram packing
image variation
JPEG-2000
JPEG-LS
linear approximation
lossless image coding
nonlinear approximation
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
9.6
Papers:
1.1W
Citations:
1.7W
Organization
No organization information available