Parallel Computations II
March 3, 2009
Parallel Image Processing
Image processing is gaining larger importance in a variety of application areas.
Active vision, e.g. for autonomous vehicles, requires substantial computational
power, in order to be able to operate in real time. Here, vision allows the
development of more
flexible and intelligent systems than any other sensor system.
In addition, there is also the need to speed up non
critical image processing
routines, e.g. in evaluating medical or satellite image data.
The ideal concept of having one processor (ALU) pe
r image pixel allows a very
simple and natural definition of image operations. In my presentation, I would like
to give an extensive overview of typical basic image processing operations,
demonstrating how they can be processed
I will exp
lain the most
important algorithms of image processing such as edge detection,
gray scale, smoothing filters, noise
reduction, segmentation, and compression.
my presentation will go through
some topics related to parallel image processing (PIP) such as
PIP techniques, PIP hardware architectures, And