JOURNAL OF COMPUTERS (JCP)
ISSN : 1796-203X
Volume : 2    Issue : 8    Date : October 2007

Spectral Interpolation on 3×3 Stencils for Prediction and Compression
Lorenzo Ibarria, Peter Lindstrom, and Jarek Rossignac
Page(s): 53-63
Full Text:
PDF (543 KB)


Abstract
Many scientific, imaging, and geospatial applications produce large high-precision scalar fields
sampled on a regular grid. Lossless compression of such data is commonly done using predictive
coding, in which weighted combinations of previously coded samples known to both encoder and
decoder are used to predict subsequent nearby samples. In hierarchical, incremental, or selective
transmission, the spatial pattern of the known neighbors is often irregular and varies from one
sample to the next, which precludes prediction based on a single stencil and fixed set of weights.
To handle such situations and make the best use of available neighboring samples, we propose a
local spectral predictor that offers optimal prediction by tailoring the weights to each configuration of
known nearby samples. These weights may be precomputed and stored in a small lookup table.
We show through several applications that predictive coding using our spectral predictor improves
compression for various sources of high-precision data.

Index Terms
interpolation, prediction, compression, spectral basis, discrete cosine transform, irregular stencils