2020-21
Onwards
(MR-20)
Code: A0440
Credits: 3
MALLA REDDY ENGINEERING COLLEGE
(Autonomous)
DIGITAL IMAGE PROCESSING
B.Tech.
VII Semester
L
T
P
3
-
-
Pre-Requisites: Digital Signal Processing.
Course Objectives: This course introduces
• The fundamentals of digital image processing,
• The concept of two dimensional transformations on spatial images,
• Application of various filtering methods for image enhancement, various image
segmentation algorithms, concepts of color image processing and different image
compression techniques.
MODULE I:
[10 Periods]
Digital Image Fundamentals
Fundamental Steps in Digital Image Processing, Components of an Image Processing
System, A Simple Image Formation Model, Image Sampling and Quantization,
Relationships Between Pixels, Imaging Geometry, Applications of Image processing.
MODULE II:
[10 Periods]
Image Transforms: 2-D Fourier Transform, Properties, FFT, Walsh Transform,
Hadamard Transform, Discrete Cosine Transform, Haar transform, Slant transform,
Hotelling transform, Properties of all the transforms.
MODULE III:
[8 Periods]
Image Enhancement
A: Spatial Domain: Introduction, Gray Level Transformations, Histogram Processing,
Arithmetic and Logic Operations, Basics of Spatial Filtering, Smoothing Spatial Filters,
Sharpening Spatial Filters, High Boost Filtering.
B: Frequency Domain: Smoothing Frequency-Domain Filters, Sharpening FrequencyDomain Filters, Homomorphic Filtering.
MODULE IV:
[10 Periods]
Image Restoration and Color Image Processing
A: Image Restoration: Image Degradation/Restoration Process, Noise Models,
Restoration in the Presence of Noise Only-Spatial Filtering, Periodic Noise Reduction by
Frequency Domain Filtering, Inverse Filtering, Minimum Mean Square Error (Wiener)
Filtering, Constrained Least Squares Filters.
B: Color Image Processing: Color Models, Pseudo-color Image Processing, Full-color
Image Processing.
Module - V:
[10 Periods]
Image Compression and Segmentation
A: Image Compression: Fundamentals, Data Redundancies, Image Compression Models,
Elements of
Information Theory, Error Free Compression techniques, Lossy
Compression techniques, Image Compression Standards.
B: Image Segmentation: Detection of Discontinuities, Edge Linking and Boundary
Detection, Thresholding, Region-Based Segmentation, Segmentation by
Morphological Watersheds
Text Books:
1. R. C. Gonzalez, R. E. Woods, “Digital Image processing”, Addison Wesley/
Pearson education, New Delhi, India, 3rd edition, 2002.
Reference Books:
1. K. Jain, “Fundamentals of Digital Image processing”, Prentice Hall of India,
New Delhi, 2nd Edition, 1997.
2. Rafael C. Gonzalez, “Digital Image processing using MATLAB”, Richard E.
Woods and Steven Low price Edition, Pearson Education Asia, India, 2nd Edition,
2004.
3. William K. Pratt, “Digital Image Processing”, John Wiley & Sons, New Delhi, India, 3rd
edition, 2004.
4. Arthur R. Weeks, Jr, “Fundamentals of Electronic Image Processing”, SPIEOptical
Engineering Press, New Delhi, India, 2nd Edition, 1996.
Course Outcomes: After completion of the course, students will be able to:
S.No
Description
CO1
CO2
CO3
CO4
CO5
BLOOMS
LEVEL
Have an appreciation of the fundamentals of Digital image processing
including the simple image formation and relationship between pixels
Implement basic DFT transform and image transforms using Image
Processing Tools
Implement basic image processing algorithms like enhancement in spatial
and frequency domain.
Analyze the different types of image degradation like linear image
restoration techniques and nonlinear image restoration techniques
Understand the need for image compression like lossy and loss less image
compression techniques and the need of image segmentation.
L2
L3
L3
L4
L2
CO- PO, PSO Mapping (3/2/1 indicates strength of correlation) 3-Strong, 2-Medium, 1-Weak
COS
CO1
CO2
CO3
CO4
CO5
PO1
PO2
PO3
PO4
Programme Outcomes(POs)
PO5
PO6
PO7
PO8
1
3
3
3
2
2
3
3
2
3
PO9
1
2
2
3
PO10
PO11
PO12
2
2
3
3
PSO1
3
3
1
3
PSOs
PSO2
3
2
2
3
PSO3
3
3
3