Design and Implementation of Adaptive Gaussian Filters for the Removal of Salt and Pepper Noise on FPGA

In recent eras of image processing, during image acquisition and transfer, images are often corrupted by impulse noise which is a major factor affecting the contents of a digital image. In fixed-value impulse noise, the gray value is a fixed value, i.e., either 0 or 255 (example: Salt and pepper noise). Digital signal processing frequently involves some method for noise reduction over an image. The median filter is a non-linear digital filter, which is most popularly used to remove impulse noises. Many popular algorithms were presented which eliminates impulse noises present and maintains the fine details of the image. But, median filter fails to preserves the edges of the image by uniform modification of the noise affected pixels and the noise-free pixels. Also, the conventional filters work better only over images affected with low noise ratios and is very poor when the noise ratio reaches above 40%. The proposed de-noising algorithm uses an adaptive Gaussian filters for removal of salt and pepper noise. As conventional de-noising algorithm fails at high noise density and in preserving edges along with image details the proposed technique switches between mask sizes depending noise density. To preserve edges and details of the image Adaptive threshold is employed. Advantage of adaptive threshold filtering does not affect the edges or other small structures in the image. Hence this method is more efficient for the images with very high noise ratio and preserving edges.