Image Processing Reference
In-Depth Information
Chapter 3
Edge-Preserving Solution
3.1 Introduction
For efficient visualization of hyperspectral image, we would like to combine as many
features from the spectral bands as possible. The features may be characterized
by the edges, boundaries, or textures. The spectral response of some materials is
possibly dominant only over a certain bandwidth. Various features in the data are thus
clearly visible and observable only over a small subset of bands in the hyperspectral
image. Typical pixel-level fusion techniques calculate the fusion weights based on
some relative importance of the pixels, also known as the saliency . In this process,
the features that are available across only a few bands may not receive adequate
representation in the final image, if the weights are not chosen carefully. Thus, the
weak features may get lost during the process of fusion. One would like to assign
comparatively higher weightage to the pixels belonging to weak features in order to
obtain a fused image where these features are appropriately represented.
The visual information is mainly available in the form of edges, lines, or
boundaries—which constitute the high frequency components in the image. Most of
the schemes of calculation of fusionweights or pixel saliency, therefore, employ some
kind of high pass filtering (HPF) to extract the necessary information. The process of
high pass filtering is equivalent to the subtraction of a suitably low pass filtered image
from the original one. A conventional low pass filtering such as Gaussian filtering,
however, distorts the edges in the image. If this low pass filtered image is used for
the calculation of fusion weights, the edges and other sharp features do not get an
appropriate representation, and hence the fused image contains visible artifacts. The
edge-preserving filters are the class of non-linear filters which manipulate the image
without distorting the boundaries and edges which are important elements of per-
ceived visual quality. Edge-preserving filters have proved to be very useful in several
applications of image processing and computer vision due to their ability to preserve
edge information. This chapter explores an application of an edge-preserving filter
known as bilateral filter for the fusion of hyperspectral image bands. We explain
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