n every image processing algorithm quality of ima ge plays a very vital role because the output of th e algorithm depends on the quality of input image. He nce, 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 cal led image enhancement algorithms. Some of the image processing algorithms use the prior knowledge of th e type of noise present in the image and are referr ed to as image restoration techniques. Image restoration techniques are also referred to as image de-noising techniques. In such cases, identified inverse degra dation functions are used to restore images. In thi s survey, we review several impulse noise removal tec hniques reported in the literature and identify eff icient implementations. We analyse and compare the perform ance of different reported impulse noise reduction techniques with Restored Mean Absolute Error (RMAE) under different noise conditions. Also, we identif y the most efficient impulse noise removing filters. Marking the maximum and minimum performance of filters helps in designing and comparing the new fi lters which give better results than the existing f ilters.