An Adaptive Filter for Image Noise Removal Using Chi-Square Goodness-of-Fit to Uniform Distribution


Noise is any undesired information that contaminates an image. The ideal situation (no noise) never occurs in practice, so there is a little point in ignoring it. Hence, one of the primary concerns of digital image processing is to increase image quality through the moderation of the degradations introduced by the noise which contaminate the image. The main 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 An Adaptive Filter Using Chi-square Goodness-of-Fit to Uniform Distribution is presented . Results shows that the proposed method removes noise from images corrupted by a variety type of noise effectively in such a manner it preserves image edges and details. The proposed method is faster than many of the traditional noise removal techniques.