Tutorial on Introduction to Digital Image Processing
Introduction to Digital Image Processing
Digital Image Processing is the implementation of mathematical methods and algorithm on
digital images for correcting, improving, analyzing and creating information.
Nowadays remote sensing data are available digitally therefore process
performed on these image also defined as digital image processing.
Image processing is combination of processes in which different techniques deployed for editing, manipulation of digital images using image processing software.
It is important to understand that the main aim of this processing is
to extract information from satellite image, which are not readily available in
satellite image, such as built up area, water body etc.
To
process satellite image digitally, the remote sensing data (i.e. satellite
images/aerial photographs) must be recorded and facilitate only in digital
form.
Instead of digital satellite images, other requirements of image
processing are computer system with appropriate hardware, image processing software and image analyst to process satellite images.
Digital image processing commonly categorize in to five broad categories:
- Pre-Processing
- Image Enhancement
- Image Transformation
- Image Classification
- Post Processing
Above
image processing steps are implemented to extract information and create user
friendly information in the form of thematic map such as land use/land cover maps.
The
digital image processing start with acquiring raw satellite images then
pre-processing performed on satellite image to remove errors such as
radiometric correction and geometric corrections. Some other processes, such as
subset, mosaic are also part of pre-processing.
Radiometric corrections include
atmospheric corrections, de-stripping etc. Whereas geometric correction, bring
the satellite image with reference to earth, which is also called georefrencing.
Next
step is to enhance the satellite image quality, it is very important process to
reduce, magnify information in satellite images. There are several process for
enhance image from basics such as contrast/brightness adjustment to advance
methods like linear/non-linear enhancement using statistical and
mathematical model. Some more processes such as filtering also used to enhance
satellite image.
Image
transformation step is used to create, manipulate satellite images for getting
more accurate information. In this mostly mathematical operators are used on
satellite images to extract significant information.
This process include, use
of arithmetic operators such as image addition, image subtraction, whereas
Fourier transformation, Tasseled cap transformation, Normalized differential
vegetation index and many more used to extract information by transforming
images.
In
the next, images are classified, which means all the pixels in the satellite image which are representing different type of features/objects assigned to a
specific class.
Such as Built up includes all the built area (residential,
commercial, Industry etc.) whereas water body covers natural and man-made both type
of water body (Lake, River, Pond, Canal, Sea etc.).
So categorization of image
pixels in to a class defined as classification. Image classification performed
using basically with two approaches, supervised and unsupervised. Both methods
are significant and important in the image classification process.
Image
post processing is an important part of digital image processing as in this
process accuracy and improvisation in classification is implemented. All the
wrongly classified pixels are modified using sieve, recode methods.
However
accuracy of classified image is assessed to determine the quality of image
classification.
After
the acceptable accuracy classified image can be defined as final output, which
is further used to create report, printout and thematic maps.
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