Evaluation of 1-D, 2-D and 3-D SPIHT coding technique for remote sensing

The Set Partitioning in Hierarchical Trees (SPIHT) is a well known lossy to lossless high performance embedded bitplane image coding algorithm which uses scalar quantization and zero-trees of transformed bidimensional (2-D) images and bases its performance on the redundancy of the significance of the coefficients in these subband hierarchical trees. In this paper, we evaluate the possibility of replacing the 2-D process by a I-D adaptation of SPIHT, which may be performed independently in each line, followed by a post compression process to construct the embedded bitstream for the image. Several strategies to construct this bitstrearn, based on both a bitplane order and a precise rate distortion computation are suggested. The computational requirements of these methods are significantly lower than those of the SPIHT. Comparative results with remote sensing volumetric data show the difficulty of reducing the distortion gap with the SPIHT by means of a post compression step. Specially remarkable is the marginal differences that the optimal rate distortion strategies achieve when compared to simple strategies like a sequential bitplane ordering of the bitstream.