Efficient image noise filtering using neural networks in unconstrained environments
Amin Farzin, Pouria Rafatnia · 2015
Scanning images, picture and other image related operation always involve the corruption of the output image due to the addition of noises. When related to imaging, noises are a high frequency random perturbation in the image pixels. You can think of noise as the subtle background hiss you hear at a stereo system at high volume. There are many methods to achieve noise elimination and reduction and total elimination can rarely be found. as a further, one of the biggest problems in noise reduction is that the more noise we would like to reduce, the blurrier the image becomes. Blurring an image as a way of reducing noise isn't always such a good idea, a blurred image makes it hard to quench between small objects in the image, not to mention the uneasiness observing that image. Finally, This project offers to reduce image noise using a Neural Network and we see that the proposed algorithm significantly affect the noise.