A tree code, asymptotically optimal for stationary Gaussian sources and squared error distortion, is applied suboptimally to encode the discrete cosine transform (DCT) of image subblocks. The variance spectrum of each block DCT is estimated and specified uniquely by a set of one-dimensional autoregressive parameters. The average pel rate for each block is allowed to vary to meet the specification of the same average distortion per block. Since the variance spectrum and rate are different for every block. so is the code tree. Comparative coding simulations with a 256*256 and 512*512 image show that DCT tree coding with postcoding is clearly superior to DCT quantization and that a variable block rate assignment gains about 3 dB over a fixed block rate assignment.>

A transform tree code, theoretically optimal for stationary Gaussian sources and the squared-error distortion measure at all rates, is adaptively applied in a blockwise fashion to the encoding of images. The rate of the basic tree code is 0.5 bits/pel and the overhead rate ranges from .24 to .36 bits/pel. A smoothing and block quantization is used for effective reduction of the rate for transmitting a set of eigenvalue estimates, which comprise the main contribution to the overhead. In encoding simulations the adaptation with smoothing and quantization gave better performance with a block size of 16 at lower search intensity and with more uniformity and less blocking effect. At a block size of 32, where the reconstruction quality is higher, the same adaptation technique yielded nearly the same results as the non-adaptive one at the same overall rate, but with a savings of search and computational complexity.