Literature Survey on Impulse Noise Reduction

In every image processing algorithm quality of image plays a very vital role because the output of the algorithm depends on the quality of input image. Hence, several techniques are used for image quality enhancement and image restoration. Some of them are common techniques applied to all the images without having prior knowledge of noise and are called image enhancement algorithms. Some of the image processing algorithms use the prior knowledge of the type of noise present in the image and are referred to as image restoration techniques. Image restoration techniques are also referred to as image de-noising techniques. In such cases, identified inverse degradation functions are used to restore images. In this survey, we review several impulse noise removal techniques reported in the literature and identify efficient implementations. We analyse and compare the performance of different reported impulse noise reduction techniques with Restored Mean Absolute Error (RMAE) under different noise conditions. Also, we identify the most efficient impulse noise removing filters. Marking the maximum and minimum performance of filters helps in designing and comparing the new filters which give better results than the existing filters.