III. DISCRETE WAVELET TRANSFORM (DWT) FEATURES
In SAR images, texture and intensity are the two important
parameters for the classification tasks. The roughness and
related textural characteristics of the soil affect the amount and
pattern of radar backscatter. Statistical texture analysis is very
important in this study since it allows better representation and
segmentation of various objects on the levee.
In this study, textural features derived from the SAR
imagery using discrete the wavelet transform (DWT) have
been used in the classification tasks. In DWT, the procedure
starts with passing the original SAR backscatter coefficients
through a set of high-pass and low-pass filters in a filter bank
followed by down sampling by a factor of two as shown in Fig.
1. The outputs from the low-pass branch are called wavelet
approximation coefficients and the outputs from the high-pass
branch are called wavelet detail coefficients. The
approximation features provide coarse textural information
from the image whereas the detail coefficients provide the
detail information.