Title :
A generalization of morphological filters using multiple structuring elements
Author :
Song, Jisheng ; Delp, Edward J.
Author_Institution :
Comput. Vision & Image Process. Lab., Purdue Univ., West Lafayette, IN, USA
Abstract :
A new class of morphological filters is proposed for smoothing an image contaminated with noise. A multiple model that includes the combination of linear and nonlinear operations is used in the design of the new filter. The performance of the averaging version of this new filter is similar to that of the alpha-trimmed mean filter. The structure-preserving properties of this new filter depend on the values assigned to the coefficients in the filter. The idempotent property is obtained when a closing-min and opening-max version of the filter is used. The root structure of the output signal is also investigated
Keywords :
computerised picture processing; filtering and prediction theory; alpha-trimmed mean filter; closing-min filter version; filter averaging version performance; filter coefficients; filter design; idempotent property; linear operations; morphological filter class; multiple model; multiple structuring elements; noise contaminated image smoothing; nonlinear operations; opening-max filter-version; output signal; root structure; structure-preserving properties; Computer vision; Filtering algorithms; Finite impulse response filter; Gaussian noise; Image edge detection; Image processing; Information filtering; Information filters; Laboratories; Nonlinear filters;
Conference_Titel :
Circuits and Systems, 1989., IEEE International Symposium on
Conference_Location :
Portland, OR
DOI :
10.1109/ISCAS.1989.100518
