The main purpose of this study is to apply the minimum noise fraction (MNF) method on the satellite
images of Gabal Um El-Guruf area in the north eastern desert of Egypt in order to remove its noise which enhances
image quality.
A minimum noise fraction (MNF) transformation is used to reduce the dimensionality of the hyper-spectral data by segregating the noise in the data. The MNF transform is equivalent to a transformation of the data to a coordinate system in which the noise covariance matrix is the identity matrix followed by a principal component transformation. The difficulty in applying the MNF technique lies in finding these covariance matrices. The grey level covariance matrix can be readily derived as the sample covariance matrix of the data and the noise covariance matrix is more complex to assess. The results show that images filtered using the MNF are superior in reducing stripes and noise.