Kk. Simhadri et al., WAVELET-BASED FEATURE-EXTRACTION FROM OCEANOGRAPHIC IMAGES, IEEE transactions on geoscience and remote sensing, 36(3), 1998, pp. 767-778
Features in satellite images of the oceans often have weak edges. Thes
e images also have a significant amount of noise, which is either due
to the clouds or atmospheric humidity. The presence of noise compounds
the problems associated with the detection of features, as the use of
any traditional noise removal technique will also result in the remov
al of weak edges. Recently, there have been rapid advances in image pr
ocessing as a result of the development of the mathematical theory of
wavelet transforms. This theory led to multifrequency channel decompos
ition of images, which further led to the evolution of important algor
ithms for the reconstruction of images at various resolutions from the
decompositions. The possibility of analyzing images at various resolu
tions can be useful not only in the suppression of noise, but also in
the detection of fine features and their classification. This paper pr
esents a new computational scheme based on multiresolution decompositi
on for extracting the features of interest from the oceanographic imag
es by suppressing the noise. The multiresolution analysis from the med
ian presented by Starck-Murtagh-Bijaoui [4], [5] is used for the noise
suppression.