Implementation of Image Deblurring Techniques in Java
Peter Chapman
Computer Systems Lab 2008
Thomas Jefferson High School for Science and Technology
Alexandria, Virginia
June 2, 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
motion blu