TITLE:      Comparison of different methods of classification in subband 
	    coding of images
AUTHORS:    R. L. Joshi, H. Jafarkani, J. H. Kasner, T. R. Fischer, 
	    N. Farvardin, M. W. Marcellin, and R. H. Bamberger
JOURNAL:    IEEE Transactions on Image Processing
ABSTRACT:
This paper investigates various classification techniques, applied to
subband coding of images, as a way of exploiting the stationary nature of
image subbands. The advantages of subband classification are characterized
in a rate-distortion framework in terms of ``classification gain'' and
overall ``subband classification gain.'' Two algorithms, maximum classification
gain and equal mean-normalized standard deviation classifications, which
allow unequal number of blocks in each class are presented. The dependence
between the classification maps from different subbands is exploited either
directly while encoding the classification maps or indirectly by constraining 
the classification maps. The trade-off between the classification gain
and the amount of side information is explored. Coding results for a
subband image coder based on classification are presented.  The simlation 
results demostrate the value of classification in subband coding.