An adaptive Gaussian filter for noise reduction and edge detection

Gaussian filtering has been intensively studied in image processing and computer vision. Using a Gaussian filter for noise suppression, the noise is smoothed out, at the same time the signal is also distorted. The use of a Gaussian filter as pre-processing for edge detection will also give rise to edge position displacement, edges vanishing, and phantom edges. Here, the authors first review various techniques for these problems. They then propose an adaptive Gaussian filtering algorithm in which the filter variance is adapted to both the noise characteristics and the local variance of the signal.<<ETX>>