DocumentCode :
2091345
Title :
A multiresolution stochastic process for image compression
Author :
Moni, Shankar ; Kashyap, R.L.
Author_Institution :
Sch. of Electr. Eng., Purdue Univ., West Lafayette, IN, USA
Volume :
4
fYear :
1996
fDate :
7-10 May 1996
Firstpage :
1954
Abstract :
We define a data structure called a “web” together with an algorithm to choose scale-space atoms for representing an image. The corresponding wavelet coefficients (of the atoms chosen using this method) have useful properties which lead to (i) the definition of a stochastic process for representing images and (ii) an efficient image compression algorithm. The advantage of our image compression algorithm is that the computational requirement is very low. The stochastic process is useful in a theoretical sense because it gives us a framework in which to understand images and certain image compression algorithms
Keywords :
data compression; data structures; image coding; image representation; image resolution; stochastic processes; transform coding; wavelet transforms; data structure; image compression algorithm; image representation; low computational requirement; multiresolution stochastic process; scale-space atoms; wavelet coefficients; web; Biomedical imaging; Catalogs; Data structures; HDTV; Image coding; Image resolution; Image storage; Multimedia systems; Stochastic processes; Wavelet coefficients;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on
Conference_Location :
Atlanta, GA
ISSN :
1520-6149
Print_ISBN :
0-7803-3192-3
Type :
conf
DOI :
10.1109/ICASSP.1996.544835
Filename :
544835
Link To Document :
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