A Statistical Image Noise Removal Adaptive Filter Using Rejection Test with F- Distribution

Abstract

The main characteristic of adaptive filters is that it alters its basic behavior as the image is processed, so it can remove noise from images regions as well as preserving edge and details information. The objective of this work is to combine the statistical analysis methods and image processing techniques to increase image quality by removing the noise that corrupts it, so that the image will be ready for analysis and interpretation. In this work a Statistical Image Noise Removal Adaptive Filter Using Rejection Test with F- Distribution is presented. The proposed filter removes noise from images corrupted by a variety type of noise effectively in such a manner it preserves image edges and details. Results shows that the proposed filter is much more accurate than many of the traditional and adaptive noise removal filters.