<title>New method of noise smoothing based on gray level and spatial separation</title>

Abstract

Medical images produced by x rays as the energy source are subject to contamination by random noise due to the statistical nature of both the x rays and the electomagnetic field. This noise degrades the image quality. There has been a considerable amount of effort devoted to the removal of noise in medical images. The purpose of this project is to introduce a new method that utilizes the natural separation of different populations of pixels with the same gray-level characteristics to smooth image noise efficiently while effectively preserving edges. The assumption is made that pixels inside a small window can be separated into two populations. Only the pixels belonging to the correct population will be used for filtering. Thus smoothing performance is enhanced while maintining the preservation of edges since pixels from the other population are not included in the evaluation. The new filter involves two steps: (1) Pixels are clustered according to their gray-level characteristics. (2) The central pixel is replaced by a weighted averaged value from the population containing the central pixel. The weight is determined by the distance of a given pixel from the central pixel. Preliminary results show effective noise smoothing especially where there is a large uniformity of pixels. Furthermore, there is preservation of edges.