A Brief Review of Image Restoration Techniques

Image restoration is an essential issue in high level image processing which deals with recovering of an original and sharp image using a degradation and restoration model. Through image acquisition process degradation occurs. Image restoration is used to estimate the unique image from the degraded data. The degradations include half toning, dithering and security watermarks. An iterative image restoration method is used to restore the severely degraded face images which improve the recognition presentation and the quality of the restored image. There are different types of image restoration techniques such wiener filter, inverse filter, regularized filter, Richardson –Lucy algorithm, neural network approach ,wavelet based approach, blind de-convolution. The fact that makes image de-noising a difficult task is uncertainties in the impulse noise. The main knowledge in dayflies is uncertainty and erratic, unfortunately it is similar to impulse noise. The mathematic implements for managing uncertainty mostly are probability theory and fuzzy mathematics. That means, amid the uncertainties involved in impulse noise, the randomness and the fuzziness are the two most important features. Keywords-Image De-blurring, Gaussian Blur, Direct inverse filtering, Weiner Filter de-blurring method, Image restoration