Title :
Convolution Morphological Filters
Author :
Duan-shan ; Qin Qian-qing
Author_Institution :
South-Central Univ. for Nationalities, Wuhan
Abstract :
In this paper, we present a novel morphological filter, called convolution morphological filters (CMF), using the linear convolution theory and method. The newly introduced filters employ a weighted convolution kernel and apply multiplication and division in place of addition and subtraction in ordinary morphological operations. The property of CMF indicates that it can smooth image and using to remove noise contained in images. An automatic generation algorithm of convolution morphological kernel is proposed, which is important to the function of CMF. Experimental results prove that an algorithm to smooth image or remove image noise is feasible and available. For some cases, the CMF act better than ordinary morphological filters.
Keywords :
convolution; filtering theory; image denoising; automatic generation algorithm; convolution morphological filters; image smoothing; linear convolution theory; noise removal; weighted convolution kernel; Computer graphics; Computer science; Convolution; Educational institutions; Filtering theory; Image processing; Kernel; Morphological operations; Morphology; Nonlinear filters;
Conference_Titel :
Image and Graphics, 2007. ICIG 2007. Fourth International Conference on
Conference_Location :
Sichuan
Print_ISBN :
0-7695-2929-1
DOI :
10.1109/ICIG.2007.74