Many digital images, especially in biomedical fields, contain some disturbances. The image analysis depends on quality of the images that is why reduction or elimination (if it is possible) the disturbances is the key issue. There are many methods of improvement in the quality of the images and thus improve the quality of the image analysis, among them one of the simplest method is low-pass filtering such as arithmetic mean or its generalization, weighted mean. The basic problem of the weighted mean is the proper selection of the weights. This can be done using adaptive algorithms. This paper presents several such algorithms which are modifications of the existing weighted averaging methods created originally for noise reduction in electrocardiographic signal. The description of the new filtering methods and a few results of its application are also presented with comparison to existing arithmetic average filtering.
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