Fixed Value Impulse Noise Removal In Medical Image By Modified Un Symmetric Trim Mean Filter

In last decade medical image quality improvement most popular topic for research. There are many methods are present for improving medical images. In the field of medical image processing, digital images very often get corrupted by several kinds of noise during the process of image acquisition. In this paper, we will present a new method for removal of impulse noise and enhancing magnetic resonance (MR) images quality. The method is based on eliminating impulse noise from MR images. A mean median-based method to remove impulse noise from digital MRI images has been developed. The method is adjusted in order to decide whether the median operation can be applied on a pixel. In this research, to suppress this deficiency, noisy pixels are initially detected, and then the filtering operation is applied on them. The proposed decision based unsymmetric mean median method (DBUMM) is simple and leads to fast filtering. The results are more accurate than other conventional filters. DBUMM detection stage a more powerful here we have use an alpha trimmed median filter for removal of noisy pixels. As a considerable advantage, some unnecessary median operations are eliminated and the number of median operations reduces drastically by using DBUMM. Decision based unsymmetric mean median filtering method leads to more acceptable results in scenarios with high noise density gives better peak signal noise ratio (PSNR) and better image quality. Furthermore, the proposed method reduces the probability of detecting noise-free pixels as noisy pixels and vice versa.