SWT -based Wavelet Filter Application for De-noising of Remotely Sensed Imageries

Wavelet scheme can be applied to the various remote sensing problems: conventional multi-resolution image analysis, compression of large image sets, fusion of heterogeneous sensor image and segmentation of features. In this study, we attempted wavelet-based filtering and its analysis. Traditionally, statistical methods and adaptive filter are used to manipulate noises in the image processing procedure. While we tried to filter random noise from optical image and radar image using Discrete Wavelet Transform (DW1) and Stationary Wavelet Transform (SW1) and compared with existing methods such as median filter and adaptive filter. In result, SWT preserved boundaries and reduced noises most effectively. If appropriate thresholds are used, wavelet filtering will be applied to detect road boundaries, buildings, cars and other complex features from high-resolution imagery in an urban environment as well as noise filtering