Image Restoration

Image Restoration

Abstract:

Any image acquired by optical ,electro-optical or electronic means is likely to be degraded by the sensing environment .The degradation may be in the form of sensor noise, blur due to the camera misfocus, relative object camera motion, random atmospheric turbulence, and so on. Image restoration is concerned with filtering the observed image to minimize the effect of degradations. The effectiveness of the image restoration filters depends on the extent and the accuracy of the knowledge of the degradation process as well as on the filter design criterion.

In this paper we have discussed various filtering techniques used for image restoration such as Wiener filter, Inverse filter, Wavelet based filter and Blind Deconvolution. A fundamental result in filtering theory used for commonly image restoration is called the Wiener filter .This filter gives the best linear mean square estimate of the object from the observation. But Weiner filter actually amplifies the noise when blurring filter is singular. This noise can be removed using Wavelet based filter.
If we know of or can create a good model of the blurring function that corrupted an image, the quickest and easiest way to restore that is by inverse filtering. The objective of the blind image restoration is to reconstruct the original image from a degraded observation without the knowledge of either the true image or the degradation process.

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