M.Sc. (Semester II) (CBCS) Examination Oct/Nov-2017
Geoinformatics
DIGITAL IMAGE PROCESSING
Day Date: Wednesday, 22-11-2017 Max. Marks: 70
Time: 10.30 AM to 01.00 PM
Instructions: All questions carry equal marks.
Q. 1 is compulsory.
Answer any two questions from Q.2, 3 4.
Answer any two questions from Q.5, 6 7.
Answer any five questions.
Q.1 Choose the alternatives given below. 14
is the remote sensing satellite series of U.S.A.
IRS SPOT
Landsat PSLV
"K-means" approach for clustering the spectral group is also called as

Kappa ISODATA
BSQ Matrix
In digital image, the intersection of each raw, I and column, J is called as

Picture Photo
FCC Pixel
In image file format, data store or data written line by line.
BIL Metadata
BIP BSQ
Errors in the image Matrix known as
RMS error Kappa Coefficient
Rectification Geometric Error
is displayed by placing the infrared, red, green in the red, green
and blue frame buffer money.
False color composition

True color Composition
Color composition None the above
Histogram minimum method is also known as technique.
Averaging Linear
Dark pixel subtraction Non Linear
errors correspond to non diagonal column elements.
Commission Omission
Kappa All of the above
Following method is not belongs to image rectification step.
Density slicing Atmospheric error
Geometric error Radiometric error
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SLR-MN-491
10) Image technique improve the quality of image for effective visual
interpretation of the various objects in the image.
Classification Enhancement
Rectification Modification
11) are the features of the known ground locations can be accurately
located on the digital image used for removing geometric error.
Map Pixel
GCP's GPS
12) In classification method the sample of the training sites is required.
Supervised Unsupervised
Image None of these
13) is the technique that convert the continuous gray tone of an
image into a series of density for each corresponding digital image.
Contrast stretch Band ratio
Density slicing Spatial filtering
14) is a widely used decision rule based on simple Boolean "and/or"
logic.
Maximum likelihood Classifier
Parallelepiped Classifier Algorithm
Minimum Distance to means classifier
None of these
Q.2 What is image? Explain the types of digital image file storage formats? 14
Q.3 Explain the sources of radiometric errors? Discuss the various methods for
removing radiometric errors.
14
Q.4 What is contrast stretch? Apply linear contrast stretching method and rearrange
the DN value of the following image.
14
80 15 25 65 10
35 20 30 45 85
70 55 10 65 95
40 60 50 35 100
105 30 90 45 75
Q.5 Write short notes on: 14
Edge Enhancement
Atmospheric Correction
Q.6 Write briefly on the following. 14
Minimum Distance to Means Classifier
Maximum Likelihood Classifier
Q.7 Write small account on: 14
Unsupervised Classification
Random Noise correction