DocumentCode :
999789
Title :
Compound image compression for real-time computer screen image transmission
Author :
Lin, Tony ; Hao, Pengwei
Author_Institution :
Nat. Lab. on Machine Perception, Peking Univ., Beijing, China
Volume :
14
Issue :
8
fYear :
2005
Firstpage :
993
Lastpage :
1005
Abstract :
We present a compound image compression algorithm for real-time applications of computer screen image transmission. It is called shape primitive extraction and coding (SPEC). Real-time image transmission requires that the compression algorithm should not only achieve high compression ratio, but also have low complexity and provide excellent visual quality. SPEC first segments a compound image into text/graphics pixels and pictorial pixels, and then compresses the text/graphics pixels with a new lossless coding algorithm and the pictorial pixels with the standard lossy JPEG, respectively. The segmentation first classifies image blocks into picture and text/graphics blocks by thresholding the number of colors of each block, then extracts shape primitives of text/graphics from picture blocks. Dynamic color palette that tracks recent text/graphics colors is used to separate small shape primitives of text/graphics from pictorial pixels. Shape primitives are also extracted from text/graphics blocks. All shape primitives from both block types are losslessly compressed by using a combined shape-based and palette-based coding algorithm. Then, the losslessly coded bitstream is fed into a LZW coder. Experimental results show that the SPEC has very low complexity and provides visually lossless quality while keeping competitive compression ratios.
Keywords :
data compression; feature extraction; image coding; image colour analysis; image resolution; image segmentation; visual communication; compound image compression; compression ratio; computer screen image transmission; dynamic color palette; graphics pixels; image blocks; image segments; lossless coding algorithm; losslessly coded bitstream; pictorial pixels; picture blocks; real-time applications; shape primitive extraction and coding; shape primitives; text pixels; visual quality; Application software; Color; Compression algorithms; Computer applications; Graphics; Image coding; Image communication; Image segmentation; Pixel; Shape; Compound image compression; compound image segmentation; palette-based coding; shape primitive extraction; shape-based coding; Algorithms; Artificial Intelligence; Computer Graphics; Computer Systems; Data Compression; Image Enhancement; Image Interpretation, Computer-Assisted; Multimedia; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated; Signal Processing, Computer-Assisted; Video Recording;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/TIP.2005.849776
Filename :
1468186
Link To Document :
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