DSP Methods for Blur Reduction in Images
Introduction
Our aim when we began this project was to examine and implement various aspects
of image restoration; that is, the removal or, more likely, the reduction, of
degradations that were inflicted while obtaining the image, while transferring
the image, or as side effects of a manipulation of the image. The primary goal
is to make the image look as close to the original image as possible, with a
minimum of blurring, noise, distortion, or other degradation.
Motivation
Perhaps the most well-known examples of the importance of image restoration are
the images acquired from the Hubble Space Telescope. Due to a flaw in the lens
system, the early images from the Hubble were far too blurred to be of any use;
however, digital image processing was used to sharpen the images by an
impressive degree.
However, image restoration can be vital in many everyday applications. For
instance, desktop scanners often blur images during acquisition. When a camera
is not held steadily enough, linear motion blur can occur. At any point in
the process of obtaining or modifying an image, noise might be added. Good
image restoration techniques can help to ameliorate all of these, and
other, problems.