Title : 
Zerotree design for image compression: toward weighted universal zerotree coding
         
        
            Author : 
Effros, Michelle
         
        
            Author_Institution : 
Dept. of Electr. Eng., California Inst. of Technol., Pasadena, CA, USA
         
        
        
        
        
            Abstract : 
We consider the problem of optimal, data-dependent zerotree design for use in weighted universal zerotree codes for image compression. A weighted universal zerotree code (WUZC) is a data compression system that replaces the single, data-independent zerotree of Said and Pearlman (see IEEE Transactions on Circuits and Systems for Video Technology, vol.6, no.3, p.243-50, 1996) with an optimal collection of zerotrees for good image coding performance across a wide variety of possible sources. We describe the weighted universal zerotree encoding and design algorithms but focus primarily on the problem of optimal, data-dependent zerotree design. We demonstrate the performance of the proposed algorithm by comparing, at a variety of target rates, the performance of a Said-Pearlman style code using the standard zerotree to the performance of the same code using a zerotree designed with our algorithm. The comparison is made without entropy coding. The proposed zerotree design algorithm achieves, on a collection of combined text and gray-scale images, up to 4 dB performance improvement over a Said-Pearlman zerotree
         
        
            Keywords : 
data compression; image coding; transform coding; trees (mathematics); wavelet transforms; Said-Pearlman style code; data compression system; data-dependent zerotree design; design algorithms; gray-scale images; image coding performance; image compression; optimal zerotree design; sources; text; wavelet decomposition; weighted universal zerotree codes; weighted universal zerotree coding; weighted universal zerotree encoding algorithms; Algorithm design and analysis; Code standards; Compression algorithms; Data compression; Discrete cosine transforms; Entropy coding; Frequency; Image coding; Switches; Training data;
         
        
        
        
            Conference_Titel : 
Image Processing, 1997. Proceedings., International Conference on
         
        
            Conference_Location : 
Santa Barbara, CA
         
        
            Print_ISBN : 
0-8186-8183-7
         
        
        
            DOI : 
10.1109/ICIP.1997.647988