Workshop Proceedings - Inter Islamic Network on Space Sciences ...

Theme 2: Agriculture Landuse
Methodology
Using antipersonnel visualization of space-based sensors
to Landsat and for periods of time successive year term
1972-1990-2001 and the study area in southern Iraq as
part of (Path 167 Row 38) was a process of Conformity
Abundant by the software Erdas 9.2 and then compare
its classification process-supervised and unsupervised
(maximum likelihood) as well as machine and process the
change detection to find out how much change in the
case of land and the amount of desert encroachment on
arable land. (Table 2)
Program uses of the ARC GIs 9.3 to produce the final map.
Table-2. The estimated degradation status of the irrigated land in Iraq,
Syria, Lebanon and Turkey
Processing of satellite images
Geometric Correction
Image Geometry Correction (often referred to
as Image Warping) is the process of digitally
Manipulating image data such that the image’s
Projection precisely matches a specific projection
Surface or shape. Image geometry correction
Compensates for the created by off-axis or screen
placement or non-flat screen surface by applying a precompensating
inverse distortion to that Image in the
digital domain. Usually, Image geometry Correction is
applied such that equal areas of projection surface.
Image geometry correction is generally implemented in
2 different ways:
1. Graphics Processing
2. Signal Processing
Both techniques involve the real time execution of a spatial
transformation from the input image to the output image,
and both techniques require powerful . The spatial
transformation must be pre-defined for a particular desired
geometric correction and may be calculated by several
different methods (more to follow) [4].
In Graphics Processing, the spatial transformation consists
of a polygon mesh (usually ). The transformation is
executed by texture mapping from the mesh of the input
image to the transformed shape of the destination image.
Each polygon on the input image is thus applied to an
equivalent (but transformed in shape and location) in
the output image [5].
Graphics Processing based Image Geometry Correction,
may be performed with inexpensive PC-based graphics
controllers. The sophisticated that uses the hardware of
a graphics controller is not a standard one, and is available
only through vendors of specialty software (i.e. Mersive
Technologies and Scalable Display Technologies). Graphics
Processing based image geometry correction is very
effective for content that originates in the PC. Its major
drawback is that it is tied to the graphics controller platform
and cannot process signals that originate outside the
graphics controller [6].
In based image geometry correction, the spatial
transformation consists of spatially defined 2-dimensional
image re-sampling or scaling filter. The scaling operation
is performed with different scaling ratios in different parts
of the image, according to the defined transformation.
Special care must be taken in the design of the scaling
filter to ensure that spatial frequencies remain balanced
in all areas of the image, and that the criterion is met in
all areas of the image. based image geometry correction
is Implemented by specially designed in the projection
system (i.e. IDT, Silicon Optix or GEO Semiconductor), or
in stand-alone Video Signal Processors (i.e. Flexible Picture
Systems) [7].
Raw Image
Are perceived by the viewer map to equal areas in the
source image. It can also be used to apply a distortion.
The term “Image” Geometry Correction, implying a
staticimage, is slightly misleading. Image geometry
correction applies to static or dynamic images (i.e. moving
video). [3]
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