21CS732 Digital Image Processing

21CS732 Digital Image Processing

Course Learning Objectives

CLO 1. Understand the fundamentals of digital image processing
CLO 2. Explain the image transform techniques used in digital image processing
CLO 3. Apply different image enhancement techniques on digital images
CLO 4. Evaluate image restoration techniques and methods used in digital imageprocessing
CLO 5. Understand the Morphological Operations and Segmentation used in digital
imageprocessing

SYLLABUS COPY

MODULE - 1

Digital Image Fundamentals: What is Digital Image Processing? Originsof Digital Image Processing,
Examples of fields that use DIP, FundamentalSteps in Digital Image Processing, Components of an Image
ProcessingSystem, Elements of Visual Perception, Image Sensing and Acquisition, Image Sampling and
Quantization, Some Basic Relationships BetweenPixels, Linear and Nonlinear Operations.

MODULE - 2

Spatial Domain: Some Basic Intensity Transformation Functions, Histogram Processing, Fundamentals
of Spatial Filtering, SmoothingSpatial Filters, Sharpening Spatial Filters


Frequency Domain: Preliminary Concepts, The Discrete FourierTransform (DFT) of Two Variables,
Properties of the 2-D DFT, Filtering inthe Frequency Domain, Image Smoothing and Image Sharpening
UsingFrequency Domain Filters, Selective Filtering.

MODULE - 3

Restoration: Noise models, Restoration in the Presence of Noise Onlyusing Spatial Filtering and
Frequency Domain Filtering, Linear, Position-Invariant Degradations, Estimating the Degradation
Function, InverseFiltering, Minimum Mean Square Error (Wiener) Filtering, ConstrainedLeast Squares
Filtering

MODULE - 4

Color Image Processing: Color Fundamentals, Color Models, Pseudo color Image Processing.
Wavelets: Background, Multiresolution Expansions.


Morphological Image Processing: Preliminaries, Erosion and Dilation, Opening and Closing, The Hitor-Miss Transforms, Some Basic Morphological Algorithms.

MODULE - 5

Segmentation: Introduction, classification of image segmentation algorithms, Detection of
Discontinuities, Edge Detection, Hough Transforms and Shape Detection, Corner Detection, Principles
of Thresholding.


Representation and Description: Representation, Boundary descriptors.

Course outcome

At the end of the course the student will be able to:
CO 1. Understand the fundamentals of Digital Image Processing.
CO 2. Apply different Image transformation techniques
CO 3. Analyze various image restoration techniques
CO 4. Understand colour image and morphological processing
CO 5. Design image analysis and segmentation techniques

Suggested Learning Resources

Textbooks
1. Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing, Third Ed., Prentice Hall,
2008.
2. S. Sridhar, Digital Image Processing, Oxford University Press, 2ndEdition, 2016


Reference
1. Digital Image Processing- S.Jayaraman, S.Esakkirajan, T.Veerakumar, TataMcGraw Hill 2014.
2. Fundamentals of Digital Image Processing-A. K. Jain, Pearson 2004

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