23-08-2012, 03:43 PM
An Introduction to Digital Image Processing with Matlab
An Introduction to Digital Image.pdf (Size: 4.22 MB / Downloads: 174)
Introduction
Images and pictures
As we mentioned in the preface, human beings are predominantly visual creatures: we rely heavily
on our vision to make sense of the world around us. We not only look at things to identify and
classify them, but we can scan for dierences, and obtain an overall rough feeling for a scene with
a quick glance.
Humans have evolved very precise visual skills: we can identify a face in an instant; we can
dierentiate colours; we can process a large amount of visual information very quickly.
However, the world is in constant motion: stare at something for long enough and it will change
in some way. Even a large solid structure, like a building or a mountain, will change its appearance
depending on the time of day (day or night); amount of sunlight (clear or cloudy), or various shadows
falling upon it.
We are concerned with single images: snapshots, if you like, of a visual scene. Although image
processing can deal with changing scenes, we shall not discuss it in any detail in this text.
For our purposes, an image is a single picture which represents something. It may be a picture
of a person, of people or animals, or of an outdoor scene, or a microphotograph of an electronic
component, or the result of medical imaging. Even if the picture is not immediately recognizable,
it will not be just a random blur.
Images and digital images
Suppose we take an image, a photo, say. For the moment, lets make things easy and suppose the
photo is monochromatic (that is, shades of grey only), so no colour. We may consider this image
as being a two dimensional function, where the function values give the brightness of the image at
any given point, as shown in gure 1.13. We may assume that in such an image brightness values
can be any real numbers in the range (black) to
(white). The ranges of and