An adaptive image smoothing technique based on localization

Image Processing are still being challenged by noises. Noise causes the intensity manipulation of the image. So, removing or reducing the noises from the image is a must before working with it. It is an active area of research because none of the established or proposed noise reducing methods can return back the original image. And also, there are different types of noises. Different proposed algorithms work fine with different types of noises and also up to a certain level of noises. In this paper, an adaptive noise removal algorithm is proposed which works fine with impulse noises and does not blur the edges of the inputted image. While removing the noises, the algorithm uses an adaptive mask which is n × n square or cross musk, n is usually an odd number. Our proposed algorithm has achieved 15.38 dB (Peak Signal to Noise Ratio) outperforming the existing filters.