Title :
Connected filters for noise removal
Author_Institution :
Dept. of Inf., Oslo Univ.
Abstract :
A class of filters for edge-preserving noise removal is presented. The basic idea is that to retain connectedness in the filter, the new pixel value is calculated from the values in a local, connected area. The method described is related to the well-known KNN (k-nearest neighbors) method. The filter is shown to behave better than the KNN filter in most situations. The filter is conceptually very simple, and thus simple to use. Its computing efficiency is comparable to that of the KNN filter
Keywords :
filtering and prediction theory; pattern recognition; KNN filter; connected filters; connectedness; edge-preserving noise removal; k-nearest neighbors; pattern recognition; Adaptive filters; Cleaning; Filtering; Image generation; Image segmentation; Informatics; Noise level; Smoothing methods; Test pattern generators; Testing;
Conference_Titel :
Pattern Recognition, 1988., 9th International Conference on
Conference_Location :
Rome
Print_ISBN :
0-8186-0878-1
DOI :
10.1109/ICPR.1988.28378
