Abstract—When an image is formed, factors such as lighting (spectra, source, and intensity) and camera characteristics (sensor response, lenses) affect the appearance of the image. Therefore, the prime factor that reduces the quality of the image is noise. It hides the important details and information‟s of images. In order to enhance the qualities of image, the removal of noises become imperative and that should not at the cost of any loss of image information. Noise removal is one of the pre-processing stages of image processing. In this paper a new method for the enhancement of gray scale images is introduced, when images are corrupted by fixed valued impulse noise (salt and pepper noise). The proposed methodology ensures a better output for low and medium density of fixed value impulse noise as compare to the other famous filters like Standard Median Filter (SMF), Decision Based Median Filter (DBMF) and Modified Decision Based Median Filter (MDBMF) etc. The main objective of the proposed method was to improve peak signal to noise ratio (PSNR), visual perception and reduction in blurring of image. The proposed algorithm replaced the noisy pixel by trimmed mean value. When previous pixel values, 0‟s and 255‟s are present in the particular window and all the pixel values are 0‟s and 255‟s then the remaining noisy pixels are replaced by mean value. The gray-scale image of mandrill and Lena were tested via proposed method. The experimental result shows better peak signal to noise ratio (PSNR), mean square error values with better visual and human perception. Keywords— Blurring, Human and visual perception, Modified Nonlinear filter, Salt and Pepper noise, Mean Square Error,Peak Signal to Noise Ratio. I. INTRODUCTION N the field of image processing, digital images very often get corrupted by several kinds of noise during the process of image acquisition. Primarily, because of the reasons like malfunctioning of pixels in camera sensors, faulty memory locations in hardware, or transmission in a noisy channel [1]. In addition, these are also the main reasons responsible for generation of the impulse noise in digital world. In the field of image processing, digital images are mainly corrupted by the impulse noise [2]. There are two types of impulse noise, Pranay Yadav is with TIT College, RGTU, Bhopal-462021, INDIA (E- mail: pranaymedc@gmail.com). Vivek Kumar is Lecturer and TPO with Laxmipati Group of Institutions, RGTU, Bhopal-462021, INDIA (Phone: +91 9098374992; e-mail: kunwarv4@gmail.com). Manju Jain was with RKDF College, RGTU, Bhopal-462021, INDIA (E- mail: manjujain87@gmail.com). Atul Samadhiya is with IES college Bhopal-462021, INDIA (e-mail: aswoodstock40@gmail.com). Sandeep Jain is with LIST college, RGTU, Bhopal-462021, INDIA (e- mail: jainsandeep10@hotmail.com). namely, the salt-and-pepper noise also known as the fixed valued impulse noise and the random-valued impulse noise [3]. Impulse noise is one the most severe noise which usually affects the images. Researchers are involved in the field of image de-noising in order to find out effective method, capable of preserving the image details, reducing the noise of digital images and ensuring the quality of the image. Image quality measurement is analyzed by image parameters like peak to single noise ratio (PSNR), mean square error (MSE), image enhancement factor (IEF), but in case of image processing one more thing of utmost importance is human perception [4]. In this paper focus is kept upon salt and pepper noise. The salt and pepper noise corrupted pixels of image take either maximum or minimum pixel value Salt and pepper noise. Fixed valued impulse noise is producing two gray level values 0 and 255. Random valued impulse noise will produce impulses whose gray level value lies within a predetermined range. The random value impulse noise is between 0 and 255. Generally the spatial domain filters have a detection stage which identifies the noisy and noise free pixels of the corrupted image, after that noise removal part removes the noise from the corrupted image under process while preserving the other important detail of image [5]. Initially standard median filter was popularly used, but later on switching based median filters came into existence which provides better results. Any other result oriented standard median filters are, weighted median filter, SD-ROM filter, centre weighted median filter, adaptive median filter, rank order median filter and many other improved filters. The performance of median filters also depends on the size of window of the filter. Larger window has the great noise suppression capability, but image details (edges, corners, fine lines) preservation is limited, while a smaller window preserves the details, but it will cause the reduction in noise suppression. Noise detection is a vital part of a filter, so it is necessary to detect whether the pixel is noise or noise free. However, further reduction in computational complexity is enviable. II. PROPOSED METHODOLOGY The proposed method deploys the enhancement by Modified Non-linear Filter (MNF) [03] algorithm. In this method first task is to detect the noisy pixels in the corrupted image. For detection of noisy pixels verifying the condition whether targeted pixel lies. If pixels are between maximum [255] and minimum [0] gray level values, then it is a noise Image De-Noising For Salt and Pepper Noise by Introducing New Enhanced Filter Pranay Yadav, Vivek Kumar, Manju Jain, Atul Samadhiya, and Sandeep Jain I International Conference on Innovations in Engineering and Technology (ICIET'2013) Dec. 25-26, 2013 Bangkok (Thailand) http://dx.doi.org/10.15242/IIE.E1213577 53