We know that when we transmit data from transmitter to receiver definitely various types of noises added automatically to our main data and it’s very tough task at the receiver side to get exact data whatever be transmitted from transmitter side. In this review paper, our focus is to remove salt and pepper noise from contaminated image. Therefore we studied various research paper and finally we came to decision that various types filters are available and every filter is used for specific types of noise means used to remove noise. In our research work, we studied the concept of restoration of the pixel. Besides this, we deeply study various research paper in which we will extract salt and pepper noise by using a filter. There are many filters used to remove noise from an image. Every filter has its own advantages and disadvantages. So we have to select which type of filter is suited for us to carry out the desired result according to our interest. Noise removal from images is a part of image restoration in which we try to reconstruct or recover an image that has been degraded by using a priori knowledge of the degradation phenomenon. Noises present in images can be of various types with their characteristic Probability Distribution Functions (PDF). Noise removal techniques depend on the kind of noise present in the image rather than on the image itself. This paper explores the effects of applying noise reduction filters having similar properties on noisy images with an emphasis on Signal-to-Noise-Ratio (SNR) value estimation for comparing the results.