Removal of Gaussian Noise in Digital Images by Immerkaer’s Fast Method using Fast and Efficient Algorithm

Image preprocessing is the technique of enhancing data images prior to computational processing. Over the past two decades, studies of photographic images represented with multi-scale multi-orientation image decompositions (loosely referred to as “wavelets”) have revealed striking nonGaussian regularities and inter and intra-subband dependencies. In this paper we propose a new fast and efficient method to remove noise. The propose method is Immerkaer’s method which denoise the image and filtering process (removing noise from images ) is done to remove noise using bilateral filter and Alpha trimmed median Filter. Bilateral filtering smooth's images while preserving edges, by means of a nonlinear combination of nearby image values. It is non-iterative, local, and simple. This method is fast and efficient method to denoise and has good quality output with high PSNR value. Here, the method first takes an input image which is a colour image and preprocessing of image is done to denoise. Preprocessing is one of the important processes in de-noising, it involves the following process removing lowfrequency background noise, normalizing the intensity of the individual particles images, removing reflections, and masking portions of images.