DocumentCode :
1696425
Title :
Lossy and lossless compression for color-quantized images
Author :
Chen, Xin ; Feng, Ju-fu ; Kwong, Sam
Author_Institution :
Nat. Key Lab. on Machine Perception, Beijing Univ., China
Volume :
1
fYear :
2001
fDate :
6/23/1905 12:00:00 AM
Firstpage :
870
Abstract :
An efficient compression scheme for color-quantized images based on progressive coding of color information has been developed. Rather than sorting color indexes into a linear list structure, a binary-tree structure of color indexes is proposed. With this structure the new algorithm can progressively recover an image from 2 colors up to all of the colors contained in the original image, i.e., a lossless recovery achieved. Experimental results show that it can efficiently compress images in both lossy and lossless cases. Typically for color-quantized Lena image with 256 colors, the algorithm achieved 0.5 bpp lower than state-of-the-art lossless compression methods while preserving the efficient lossy compression. Such a compression scheme is very attractive to many applications that require the ability to fast browsing or progressive transmission, and if necessary, to exactly recover the original image
Keywords :
data compression; entropy codes; image coding; image colour analysis; quantisation (signal); visual communication; binary-tree structure; color indexes; color information; color-quantized image; color-quantized images; context based entropy coding; fast browsing; lossless compression; lossless image recovery; lossy compression; original image recovery; progressive coding; progressive transmission; Color; Computational complexity; Computer science; Decoding; Geographic Information Systems; Image coding; Image databases; Laboratories; Pixel; Sorting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2001. Proceedings. 2001 International Conference on
Conference_Location :
Thessaloniki
Print_ISBN :
0-7803-6725-1
Type :
conf
DOI :
10.1109/ICIP.2001.959184
Filename :
959184
Link To Document :
بازگشت