GIS

2.  Image processing refers to processing of a 2D
picture by a computer.
 Image processing is used to
(i) extract information
(ii) emphasize or de emphasize certain aspects of
the information contained in the image
(iii) perform statistical or other analyses to extract
non image information

3.  In humans, the lens focuses light from objects onto
the retina.
 The retina is covered with light receptors called
cones (6-7 million) and rods (75-150 million).
 Cones are concentrated around the fovea and are
very sensitive to colour.Rods are more spread out
and are sensitive to low levels of illumination.
 Muscles within the eye can be used to change the
shape of the lens allowing us focus on objects that are
near or far away.
 An image is focused onto the retina causing rods and
cones to become excited which ultimately send
signals to the brain.

4.  Image processing systems require that the images be
available in digitized form.
 An image is continues w.r.to x ,y coordinates and
amplitude. Converting an image to digitized form
requires that the coordinates as well as the amplitude
to digitized .
 Digitizing the coordinate values is called sampling
 Digitizing amplitude values is called quantization.
 For digitization, the given Image is sampled on a
discrete grid and each sample or pixel is quantized
using a finite number of bits.
 The digitized image is processed by a computer.

5.  Digital Image Processing is
largely concerned with four basic
operations:
 image restoration
 image enhancement
 image classification
 image transformation.

6.  Image restoration is concerned
with the correction and
calibration of images in order to
achieve as faithful a
representation of the earth
surface as possible.

7.  Image enhancement is the process
of adjusting digital images so that
the results are more suitable for
display or further image analysis.
 For example, you can remove noise,
sharpen, or brighten an image,
making it easier to identify key
features.

8.  Image classification refers to the
computer-assisted interpretation of
images
 Image classification is the process
of assigning land cover classes to
pixels.
 For example, classes include water,
urban, forest, agriculture and
grassland.

9.  Image transformation refers to
the derivation of new imagery as
a result of some mathematical
treatment of the raw image
bands.

10.  Visual image interpretation is Process of identifying
what we see on the images and communicate the
information obtained from these images to others for
evaluating its significance.
 The analysis of remote sensing imagery involves the
identification of various targets in an image, and those
targets may be environmental or artificial features
 Recognizing targets is the key to interpretation and
information extraction.
 Observing the differences between targets and their
backgrounds involves comparing different targets based
on the visual elements of tone, shape, size, pattern,
texture, shadow, and association.
 Identifying targets in remotely sensed images based on
these visual elements allows us to further interpret and
analyze.

11. Tone/Colour
 Tone/Colour: - Tone refers to the relative brightness or
colour of objects on photographs.
 Real world materials like vegetation, water and bare soil
reflect different proportions of energy in the green , blue,
red, and infrared portions of the electro-magnetic
spectrum.
 An interpreter can document the amount of energy
reflected from each at specific wavelengths to create
a spectral signature.
 These signatures can help to understand why certain
objects appear as they do on black and white or colour
imagery. These shades of gray are referred to as tone.

12.  Size:- Size of objects in an image is a function
of scale. Most commonly, length, width and
perimeter are measured.
 It is important to assess the size of a target
relative to other objects in a scene, to aid in the
interpretation of that target.

13. Shape
 Shape:- Shape refers to the general form, structure, or
outline of individual objects.
 Straight edge shapes typically represent urban or
agricultural (field) targets, while natural features, such
as forest edges, are generally more irregular in shape.
In the case of stereoscopic photographs, the
object's height also defines its shape.

14.  Pattern:- Pattern relates to the spatial
arrangement of objects. The objects may be
arranged randomly or systematically. They can
be natural or man-made.
 The repetition of certain general forms or
relationships is characteristic of many objects
and gives objects a pattern that aids the photo
interpreter in recognising them.

15. Association
 Association:- refers to the occurrence of certain features
in relation to others.
 Association takes into account the relationship
between other recognizable objects or features in
proximity to the target of interest. The identification
of features that one would expect to associate with
other features may provide information to facilitate
identification.

16.  Texture:-Texture is the frequency of tonal
change on the photographic image.
 It is a product of their individual shape, size,
pattern, shadow and tone. It determines the
overall visual smoothness or coarseness of
image features.
 As the scale of the photograph is reduced, the
texture of any given object or area becomes
progressively finer and ultimately disappears.

17. Shadow
 Shadow :-usually a visual obstacle for image
interpretation.
 Gives height information about towers, tall
buildings

18.  Site:- Site refers to topographic or geographic
location and is a particularly important aid in
the identification of vegetation types.
 Site has unique physical characteristics which
might include elevation, slope, and type of
surface cover

19.  Image rectification is a transformation process used to
project two-or-more images onto a common image plane.
 It corrects image distortion by transforming the image
into a standard coordinate system.
 It is used in GIS to merge images taken from multiple
perspectives into a common map coordinate system.
 Image rectification in GIS converts images to a standard
map coordinate system. This is done by matching
ground control points (GCP) in the mapping system to
points in the image.
 Primary difficulties in the process occur
(i) the accuracy of the map points are not well known
(ii) the images lack clearly identifiable points to
correspond to the maps.

20.  Image enhancement is the improvement of digital
image quality, without knowledge about the source of
degradation.
 Enhancement refers to sharpening of image features
such as boundaries, or contrast to make a graphic
display more useful for display & analysis.
 This process does not increase the inherent
information content in data.
 It includes gray level & contrast manipulation, noise
reduction , edge crispening and sharpening, filtering,
interpolation and magnification, pseudo colouring,
and so on.
 Image enhancement is concerned with the
modification of images to make them more suited to
the capabilities of human vision.
 Enhancement methods tend to be problem specific.

22.  Traditionally, software for digital imaging has
been targeted at either manipulating or
processing images, either for practitioners and
designers or software programmers, with quite
different requirements.
 Software packages for manipulating images,
such as adobe Photoshop, corel paint and others,
usually offer a convenient user interface and
large number of readily available functions and
tools for working with images interactively.
 Sometimes it is possible to extend the standard
functionality by writing scripts or adding self –
programmed components.

23.  Two categories
(1) supervised image classification and
(2) unsupervised image classification.
 In supervised image classification training stage is
required, which means first we need to select some
pixels form each class called training pixels.
 Find the characteristics of training pixels and also
find other pixels which have same characteristics,
this way image classification can be done.
 In unsupervised image classification, no training
stage is required, but different algorithms are used
for clustering.

24.  In real world, sometimes image does not have much
information about data. So, in this case we can use
unsupervised image classification as here information
is not required before classification, unlike supervised
classification.
 Factors affect the classification results are objective of
classification, the spectral and spatial characteristics of
the data, natural variability of terrain conditions in
geographic region, and the digital classification
technique employed.
 The success of an image classification depends on
many factors likes availability of high-quality remotely
sensed imagery and ancillary data, the design of a
proper classification procedure, and the analyst’s skills
and experiences etc.

25.  A hybrid measurement technique is proposed
for high-precision surface inspection.
 The technique uses an interferometer to image
microscopic surface defects.
 In order to quantify the degree of various
surface defects, the interferograms are scanned,
digitized, and subsequently converted to a
binary image by using an adaptive
thresholding technique which takes into
account the inhomogeneity of the imaging
system

26.  Classified data often manifest a salt-and-pepper
appearance due to the inherent spectral variability
encountered by a classification when applied on a
pixel-by pixel basis.
 It is often desirable to “smooth” the classified output to
show only the dominant (presumably correct)
classification.
 One means of classification smoothing involves the
application of a majority filter.
 In such operations a moving windows is pass through
the classified pixel in the window is not the majority
class, its identity is changed to the majority class.

27.  If there is no majority class in the window, the identity
of the center pixel is not changed. As the windows
progresses through the data set, the original class code
are continually used, not the labels as modified from
the previous window position.
 Majority filters can also incorporate some from of class
and/or spatial weighting function. Data may also be
smoothed mote than once.
 Certain algorithms can preserve the boundaries
between land cover regions and also involve a user-
specified minimum area for any given land cover type
that will be maintained in the smooth output.

28.  Accuracy assessments determine the quality of the
information derived from remotely sensed data.
 Assessments are a complex subject and a fairly
immature one.
 Assessments can be either qualitative or quantitative.
 In qualitative assessments, we determine if a map
"looks right" by comparing what we see in the imagery
with what we see on the ground. This is not usually
done in a rigorous way, but rather in a "quick and
dirty" way.
 General accuracy is the goal in this case, and error and
its sources are not as important. This is usually a first
cut assessment.

29.  Quantitative assessments attempt to identify
and measure remote sensing-based map error.
 In such assessments, we compare map data
with reference or ground truth data (where
ground truth data is to be 100% correct).
 Two types of accuracy
location accuracy and classification accuracy
 There are basically two types of data collected
in support of remote sensing accuracy
assessments: other remote sensing data (most
commonly aerial photos) and ground-based
data.

30.  The merging of multisensor data through intensity, hue,
and saturation colour transform (IHS) has been mainly
used to produce hybrid products with high spatial
resolution, which enhance terrain features.
 The method is related to the human colour perception
parameters, defined in terms of intensity (brightness of
the colour), hue (dominant colour: red, green, blue, and
colour mixtures), and saturation (purity of the colour).
 The procedure involves the transfer of the colour
parameters from images originally displayed in the red-
green-blue domain, to the IHS colour space.
 The reverse transform to the RGB domain permits the
IHS images to be replaced by new images. In order to
ensure a precise matching, Landsat images and the aerial
photograph were co-registered, this time using the aerial
photograph as a reference.

31.  Through this procedure, Landsat images were
resampled, by nearest-neighbor method, to the same
resolution of the aerial photograph (pixel size of 6 by 6
meters).
 After these corrections, intensity, hue, and saturation
values were calculated from the TM1, TM2, and TM3
bands.
 In the reverse transform to the RGB domain, the image
was replaced by the aerial photograph.
 The resultant hybrid image keeps the spatial resolution
of the aerial photograph and the spectral information of
the Landsat-TM bands.
 Due to the high spatial resolution of the aerial
photograph/ Landsat-TM hybrid images, the terrain
features produced intricate patterns, making the visual
interpretation quite difficult.
 In order to overcome this problem and to facilitate the
generation of a thematic map of the terrain features,
segmentation and region-classification techniques were
applied to the hybrid images.

32.  A GIS makes it possible to link, or integrate, information
that is difficult to associate through any other means.
 Thus, a GIS can use combinations of mapped variables to
build and analyze new variables. Data integration is the
linking of information in different forms through a GIS.
 For example, using GIS technology, it is possible to
combine agricultural records with hydrography data to
determine which streams will carry certain levels of
fertilizer runoff.
 Agricultural records can indicate how much pesticide
has been applied to a parcel of land. By locating these
parcels and intersecting them with streams, the GIS can
be used to predict the amount of nutrient runoff in each
stream.
 Then as streams converge, the total loads can be
calculated downstream where the stream enters a lake.

33.  The scale is differently defined in different disciplines.
 In the remote-sensing opinion, the scale is measured
from the sky to the Earth's space measurement range
(spatial scale), the time interval (time scale) and the
width of the spectrum (spectral measure).
 The spatial scale of the remote sensing concluding two
main meanings, which are the image spatial resolution
and spatial extent of surface.
 In remote-sensing field, the spatial resolution and the
scale is corresponded, the current study on the remote-
sensing size affection, is mainly in the change of the
image spatial resolution caused by the pixel scale
changes.

34.  This ignores the scale effect of remote-sensing
applications, which is overlooked by the spatial
extent of changes in image scale effect.
 After blocking, the total coverage of all images
and the effective number of pixel are unchanged,
the total pixel number of single-image is
dependent on the coverage of each image.
 As the coverage changes, the image block must
be to lead to the mean value changing.
 Therefore, during the process of image
segmentation, the size effect caused by the
calculation of analytical error must be
considered.

35.  An image data compression system that uses
progressive transmission is one that allows a user to
reconstruct successively higher delity versions of an
image as data are received.
 The goal of progressive transmission is thus not only
efficient overall compression, but efficient
compression at every step.
 If the data rate available for image transmission is
unexpectedly low, or if the volume of compressed
data exceeds expectations, the available rate will be
used to its full extent, to provide nearly the highest-
delity image possible given the rate constraint.

36.  Alternatively, if the available rate exceeds expectations,
it will be possible to send higher-resolution images
than originally planned.
 In this sense, progressive transmission strategies are
robust with respect to the available data rate.
 In situations where the reverse channel can be used,
data compression can be combined with advanced
communications strategies to increase the volume of
data returned.
 The use of retransmission schemes is one example of
such a strategy.
 Progressive transmission gives another method,
because it provides the ability to quickly view low- or
medium-resolution previews of an image, making
efficient browsing.

37.  Image compression is concerned with minimizing
the number of bits required to represent an image.
 Application of compression are in broadcast TV,
remote sensing via satellite, military communication
via aircraft, radar, teleconferencing, facsimile
transmission, for educational & business documents,
medical images that arise in computer tomography,
magnetic resonance imaging and digital radiology,
motion, pictures, satellite images, weather maps,
geological surveys and so on.
 The ratio of the original, uncompressed image file
and the compressed file is referred to as the
compression ratio.