<< Chapter < Page Chapter >> Page >
The module provides an introduction into the concepts of image restoration and filtering.

Image restoration

In many applications ( e.g. , satellite imaging, medical imaging, astronomical imaging, poor-qualityfamily portraits) the imaging system introduces a slight distortion. Often images are slightly blurred and imagerestoration aims at deblurring the image.

The blurring can usually be modeled as an LSI system with a given PSF h m n .

Fourier Transform (FT) relationship between the two functions.

The observed image is

g m n h m n f m n
G u v H u v F u v
F u v G u v H u v

Image blurring

Above we showed the equations for representing the common model for blurring an image. In we have an original image and a PSF function that we wish to apply to the image in order to model a basicblurred image.

Once we apply the PSF to the original image, we receive our blurred image that is shown in :

Got questions? Get instant answers now!

Frequency domain analysis

looks at the original images in its typical form; however, it is often useful tolook at our images and PSF in the frequency domain. In , we take another look at the image blurring example above and look at how the imagesand results would appear in the frequency domain if we applied the fourier transforms.

Get Jobilize Job Search Mobile App in your pocket Now!

Get it on Google Play Download on the App Store Now




Source:  OpenStax, Fundamentals of signal processing. OpenStax CNX. Nov 26, 2012 Download for free at http://cnx.org/content/col10360/1.4
Google Play and the Google Play logo are trademarks of Google Inc.

Notification Switch

Would you like to follow the 'Fundamentals of signal processing' conversation and receive update notifications?

Ask