Title :
On empirical estimation of the parameters of edge enhancement filters
Author :
Farag, Aly A. ; Cao, Yu ; Rose, D.M. ; Delp, Edward J.
Author_Institution :
Dept. of Eng. Math. & Comput. Sci., Louisville Univ., KY, USA
Abstract :
The authors develop an empirical measure for the selection of the Gaussian filter that is commonly used for edge enhancement. The measure is based totally on the image at hand. Edge enhancement by a Gaussian filter has two distinct advantages: (1) the filter is fully described by a single parameter, the standard deviation σ; (2) the two-dimensional filter is separable and can be easily implemented. The filter´s spatial support is a function of σ. This support is normally in the range of ±3.5 σ. An empirical measure is described for the selection of the Gaussian filter´s spatial support using the power spectrum density of the input image. Classic Fourier analysis is used to obtain a measure for the spatial support of the Gaussian filter given a particular image. Experimental results suggest that this measure can be used as an aid in deciding the Gaussian filter´s spatial support needed to enhance the edges
Keywords :
edge detection; filtering and prediction theory; parameter estimation; Fourier analysis; Gaussian filter; edge enhancement filters; empirical parameter estimation; power spectrum density; standard deviation; two-dimensional filter; Density functional theory; Frequency estimation; Image edge detection; Image segmentation; Joining processes; Low pass filters; Mathematics; Parameter estimation; Shape; Smoothing methods;
Conference_Titel :
Systems, Man and Cybernetics, 1992., IEEE International Conference on
Conference_Location :
Chicago, IL
Print_ISBN :
0-7803-0720-8
DOI :
10.1109/ICSMC.1992.271751
