Implementation of Image Deblurring
Techniques in Java
Peter Chapman
Computer Systems Lab 2007-2008
Thomas Jefferson High School for Science and Technology
Alexandria, Virginia
April 2, 2008
Abstract
Families, friends, professionals, and enthusiasts take countless num-
bers of photographs every day, and inevitably, many images suffer from
some sort of distortion, or ”blurring.” A program with the power to
take a blurred image and create a much crisper and clearer ”deblurred”
version would be immensely valuable to many fields. Law enforce-
ment agencies, for example, attempting to read the license plate from
a blurred photo, or a family attempting to improve the clarity of their
grandfather’s smile would find such a piece of software useful.
In
my implementation, I attempt to deblur images suffering from simple
types of motion blur using the alternate domains granted by the use
of Fourier transformations and a basic understanding of image decon-
volution.
Keywords: Fourier Transformations, Spatial Domain, Frequency Do-
main, Phase Domain, Blind Image Deconvolution, Fast Fourier Trans-
formation, Cooley-Turkey Fast Fourier Transformation Algorithm, Dis-
crete Fourier Transformation, Image Deblurring, Inverse Filtering
1 Introduction
Photographs are utilized in many different fields for a wide variety of pur-
poses, and regardless of the subject area, a blurred image is often a useless
1
one. A program with the ability reverse these damages would be extremely
useful. Such functionality could be bundled into the software of consumer
cameras with adjustments performed automatically after each shot, or per-
haps, an available feature on standard photo manipulation software. Due to
the complexities involved in the image deblurring process my research is fo-
cused on blind image deconvolution, where the application is given a general
overview of how the image was blurred, presumably by the user. In order to
further simplify the project further, my application is only built to handle
images suffering simple types of motion