PHLST with adaptive tiling and its application to Antarctic remote sensing image approximation (with Z. Zhang), Inverse Problems and Imaging, vol.8, no.1, pp.321-337, 2014.
We propose an efficient nonlinear approximation scheme using the
Polyharmonic Local Sine Transform (PHLST) of Saito and Remy
combined with an algorithm to tile a given image automatically and
adaptively according to its local smoothness and singularities.
To measure such local smoothness, we introduce the so-called
local Besov indices of an image, which is based on the pointwise
modulus of smoothness of the image. Such an adaptive tiling of an
image is important for image approximation using PHLST because PHLST
stores the corner and boundary information of each tile and consequently
it is wasteful to divide a smooth region of a given image into a set of
We demonstrate the superiority of the proposed algorithm
using Antarctic remote sensing images over the PHLST using the
uniform tiling. Analysis of such images including their efficient
approximation and compression has gained its importance due to
the global climate change.
Get the full paper: PDF file (final version on 10/24/13).
Get the official version via doi:10.3934/ipi.2014.8.321.
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