There are a lot of noise factors which will influence the target detection of satellite imagery as utilizing feature extraction. However, those noises are not all categorized to be useless information. As the targets are interfered by noises, those target information are also hidden inside the noise signals. In order to extract the target information and achieve the completely interpretation of targets, there is a novel noise effect removing approach has been proposed in this paper. By using the noise effect removal algorithm, those neighboring pixels around the noises are manipulated with the calculation of eigenvalue and covariance. Through the manipulation, the noise signal could be exactly described and eliminated to decrease its impacting effect. The proposed algorithm not only has been testified on the EO-1 imagery, but also testified on some hyperspectral imagery. Experimental results demonstrate the feasibility and validity of our proposed method in detecting those feature and targets. It could be applied to those areas such as national defense, environment surveillance, land planning, commercial application, and etc.
