Implementation of Image Deblurring Techniques in Java
Peter Chapman
Computer Systems Lab 2007-2008
Thomas Jefferson High School for Science and Technology
Alexandria, Virginia
May 23, 2008
Abstract
Families, friends, professionals, and enthusiasts take
countless numbers of photographs every day, and in-
evitably, many images suffer from some sort of distor-
tion, 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 enforcement 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 deconvolution.
Keywords: Fourier Transformations, Spatial Do-
main, Frequency Domain, Phase Domain, Blind
Image Deconvolution, Fast Fourier Transformation,
Cooley-Turkey Fast Fourier Transformation Algo-
rithm, Discrete Fourier Transformation, Image De-
blurring, Inverse Filtering
1 Introduction
Photographs are utilized in many different fields for
a wide variety of purposes, and regardless of the sub-
ject area, a blurred image is often a useless one. A
program with the ability reverse these damages would
be extremely useful. Such functionality could be bun-
dled into the software of consumer cameras with ad-
justments performed automatically after each shot,
or perhaps, an available feature on standard photo
manipulation software. Due to the complexities in-
volved in the image deblurring process my research is
focused on blind image deconvolution, where the ap-
plication is given a general overview of how the image
was blurred, presumably by the user. In order to fur-
ther simplify the project further, my application is
only built to handle images suffering simple types of
motio