[Show abstract][Hide abstract] ABSTRACT: The S-transform is an invertible time-frequency spec-tral localization technique which combines elements of wavelet transforms and short-time Fourier transforms. In previous usage, the frequency dependence of the ana-lyzing window of the S-transform has been through hor-izontal and vertical dilations of a basic functional form, usually a Gaussian. In this paper, we present a gener-alized S-transform in which two prescribed functions of frequency control the scale and the shape of the analyz-ing window, and apply it to determining P-wave arrival time in a noisy seismogram. The S-transform is also used as a time-frequency filter; this helps in determining the sign of the P arrival.
[Show abstract][Hide abstract] ABSTRACT: The presence of speckle in radar images makes the radiometric and
textural aspects less efficient for class discrimination. Many adaptive
filters have been developed for speckle reduction, the most well known
of which are analyzed. It is shown that they are based on a test related
to the local coefficient of variation of the observed image, which
describes the scene heterogeneity. Some practical criteria are
introduced to modify the filters in order to make them more efficient.
The filters are tested on a simulated synthetic aperture radar (SAR)
image and an SAR-580 image. As was expected, the new filters perform
better, i.e. they average the homogeneous areas better and preserve
texture information, edges, linear features, and point target responses
better at the same time. Moreover, they can be adapted to features other
than the coefficient of variation to reduce the speckle while preserving
the corresponding information
IEEE Transactions on Geoscience and Remote Sensing 12/1990; · 3.47 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Some of the well-known adaptive speckle reduction filters are
evaluated and compared based on objective and practical criteria. The
performance of the filters is tested by using both the acquired SAR
images and computer simulated patterns
Geoscience and Remote Sensing Symposium, 1994. IGARSS '94. Surface and Atmospheric Remote Sensing: Technologies, Data Analysis and Interpretation., International; 09/1994
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