Image Estimation and Restoration
Here, we apply the linear systems and basic image processing knowledge of the previous chapters to modeling, developing solutions, and experimental testing of algorithms for two dominant problems in digital image processing: image estimation and image restoration. By image estimation we mean the case where a clean image has been contaminated with noise, usually through sensing, transmission, or storage. We will treat the independent and additive noise case. The second problem, image restoration, means that in addition to the noise, there is some blurring due to motion or lack of focus. We attempt to “restore” the image in this case. Of course, the restoration will only be approximate.
We first develop ...
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