2. Syllabus
◦ Unit 1: Digital Image Processing Systems: Introduction to structure of human eye, Image formation in the
human eye, Brightness adaptation and discrimination, Image sensing and acquisition, storage, Processing,
Communication, Display Image Sampling and quantization, Basic relationships between pixels.
◦ Unit 2: Image Transforms(implementation): Introduction to Fourier transform, DFT and 2-D DFT, Properties
of 2-D DFT, FFT, IFFT, Walsh transform, Hadamard transform, Discrete cosine transform, Slant transform,
Optimum transform: Karhunen-Loeve (Hotelling) transform.
◦ Unit 3: Image Enhancement in the Spatial and Frequency Domain: Gray level transformations, Histogram
processing, Arithmetic and logic operations, Spatial filtering: Introduction, Smoothing and sharpening filters.
Frequency domain filters: Homo morphic filtering.
◦ Unit 4: Image Data Compression: Fundamentals, Redundancies: Coding, Inter pixel Psycho-visual,
fidelity criteria, Image compression models, Error free compression, Lossy compression, Image compression
standards: Binary image and Continuous Tone Still Image compression standards, Video compression
standards.
◦ Unit 5: Morphological Image Processing: Introduction, Dilation, Erosion, Opening, closing, Hit or miss
transformation, Morphological algorithm operations on binary Images, Morphological algorithm operations on
gray-scale Images.
◦ Unit 6: Image Segmentation, Representation and Description: Detection of discontinuities, Edge linking
and Boundary detection, Thresholding, Region based segmentation, Image Representation schemes,
Boundary descriptors and Regional descriptors.
3. BLOOM’S TAXONOMY COURSE OUTCOME OF DIGITAL IMAGE PROCESSING
LEVEL
1
REMEMBER
Recall facts and
basic concepts
CO 1
Remember the types of image enhancement techniques, compression
techniques, morphological processing, segmentation techniques.
LEVEL
2
UNDERSTAND
Explain ideas or
concepts
CO 2
Understanding the Image fundamentals and different techniques for
processing.
LEVEL
3
APPLY
Use information
learnt to solve a
problem
CO 3
Applying different types of image processing techniques and different
transforms on image.
LEVEL
4
ANALYSE
Understand
relationships,
causes and actions
CO 4
Analyzing the transform methods and different types of image processing
techniques.
LEVEL
5
EVALUATE
Evaluate the
correctness of
decision made
CO 5
Evaluate the methodologies for image segmentation, compression,
restoration etc.
LEVEL
6
CREATE
Create something
new
CO 6
Creating an algorithm to generate a binary image from the given sample
image.
5. CO 1
REMEMBER
CO 2
UNDERSTAN
D
CO 3
APPLY
CO 4
ANALYSE
CO 5
EVALUATE
CO 6
CREATE
Module 1
Introduction to structure of
human eye, Image formation
in the human eye,
Brightness adaptation and
discrimination, Image
sensing and acquisition,
storage, Processing,
Communication, Display
Image Sampling and
quantization, Basic
relationships between
pixels.
6. CO 1
REMEMBER
CO 2
UNDERSTAN
D
CO 3
APPLY
CO 4
ANALYSE
CO 5
EVALUATE
Module 2
Introduction to Fourier
transform, DFT and 2-D
DFT, Properties of 2-D DFT,
FFT, IFFT, Walsh
transform, Hadamard
transform, Discrete cosine
transform, Slant transform,
Optimum transform:
Karhunen-Loeve
(Hotelling) transform.
7. Module 3
Gray level transformations,
Histogram processing, Arithmetic
and logic operations, Spatial
filtering: Introduction, Smoothing
and sharpening filters. Frequency
domain filters: Homo morphic
filtering.
CO 1
REMEMBER
CO 2
UNDERSTAN
D
CO 3
APPLY
CO 4
ANALYSE
CO 5
EVALUATE
CO 6
CREATE
8. Module 4
Coding, Inter pixel Psycho-visual,
fidelity criteria, Image compression
models, Error free compression,
Lossy compression, Image
compression standards: Binary image
and Continuous Tone Still Image
compression standards, Video
compression standards.
CO 1
REMEMBER
CO 2
UNDERSTAN
D
CO 3
APPLY
CO 4
ANALYSE
CO 5
EVALUATE
CO 6
CREATE
9. Module 5
Introduction, Dilation, Erosion,
Opening, closing, Hit or miss
transformation, Morphological
algorithm operations on binary
Images, Morphological algorithm
operations on gray-scale Images.
CO 1
REMEMBER
CO 2
UNDERSTAN
D
CO 3
APPLY
CO 4
ANALYSE
CO 5
EVALUATE
CO 6
CREATE
10. Module 6
Detection of discontinuities, Edge
linking and Boundary detection,
Thresholding, Region based
segmentation, Image Representation
schemes, Boundary descriptors and
Regional descriptors.
CO 1
REMEMBER
CO 2
UNDERSTAN
D
CO 3
APPLY
CO 4
ANALYSE
CO 5
EVALUATE
CO 6
CREATE
11. 1. What is digital image processing??
(or)
Write the name of different image
transforms
2. What are the advantages of image
transforms?
(or)
What is the requirement of a canonical
cover?
REMEMBER – CO1
UNDERSTAND – CO2
Module 1
REMEMBER – CO1
Module 2
Module 2
UNDERSTAND – CO2
Module 3
12. Find out the Walsh transform coefficients for
the following samples of 1-D signal.
f(0) = 2, f(1) = 1, f(2) = 3, f(3) = 5.
Why do transforms like DCT, DFT etc. are
preferred over K-L transforms from practical
implementation considerations.
2. What are the advantages of image
transforms?
(or)
What is the requirement of a canonical cover?
UNDERSTAND – CO2
Module 2
UNDERSTAND – CO2
Module 3
APPLY – CO 3
Module 2
ANALYSE – CO 4
Module 2
13. Looking at the employee database of an office, the computer needs to create a new table with
unique employee names appearing only once and the number of occurrences of each name by
its side?
For eg: if the employee table contains the names
AB CD EF GH CD IJ CD GH AB AB EF AB,
Then the output table will be
AB 4 CD 3 EF 2 GH 2 IJ 1
Will Relational Algebra or Tuple Calculus be better in terms of ease of
expression?
Write relational algebra expression and tuple calculus expression for
the same.
In this case which expression will be easier to convert into SQL
query?
Write the SQL query
Design a new form of expression (combining relational algebra, tuple
calculus and domain calculus) to explore the ease of writing the
expression and convert it to SQL query.
ANALYSE – CO 4
APPLY – CO 3
EVALUATE – CO
5
APPLY – CO 3
CREATE – CO 6
