DIGITAL IMAGE PROCESSING (18CS741)

DIGITAL IMAGE PROCESSING

Course Code:18CS741
CIE Marks:40
Number of Contact Hours/Week:3:0:0
SEE Marks:60
Total Number of Contact Hours:40
Exam Hours:03
CREDITS –3

Course Learning Objectives: This course (18CS741) will enable students to:

• Define the fundamental concepts in image processing
• Evaluate techniques followed in image enhancements
• Illustrate image segmentation and compression algorithms

Module 1

Introduction Fundamental Steps in Digital Image Processing, Components of an Image Processing System, Sampling and Quantization, Representing Digital Images (Data structure), Some Basic Relationships Between Pixels- Neighbors and Connectivity of pixels in image, Examples of fields that uses digital mage processing
Textbook 1: Ch.1.3 to 1.5, Ch. 2.4,2.5
RBT: L1, L2

Notes will be uploaded soon

Module 2

Image Enhancement In The Spatial Domain: Some Basic Gray Level Transformations, Histogram Processing, Enhancement Using Arithmetic/Logic Operations, Basics of Spatial Filtering, Smoothing Spatial Filters, Sharpening Spatial Filters, Combining Spatial Enhancement Methods.
Textbook 1: Ch.3
RBT: L1, L2, L3

Notes will be uploaded soon

Module 3

Image Enhancement In Frequency Domain: Introduction, Fourier Transform, Discrete Fourier Transform (DFT), properties of DFT , Discrete Cosine Transform (DCT), Image filtering in frequency domain.
Textbook 1: Ch.4.1,4.2
RBT: L1, L2, L3

Notes will be uploaded soon

Module 4

Image Segmentation: Introduction, Detection of isolated points, line detection, Edge detection, Edge linking, Region based segmentation- Region growing, split and merge technique, local processing, regional processing, Hough transform, Segmentation using Threshold.
Textbook 1: Ch.10.1 to 10.3
RBT: L1, L2, L3

Notes will be uploaded soon

Module 5

Image Compression: Introduction, coding Redundancy, Inter-pixel redundancy, image compression model, Lossy and Lossless compression, Huffman Coding, Arithmetic Coding, LZW coding, Transform Coding, Sub-image size selection, blocking, DCT implementation using FFT, Run-length coding.
Textbook 1: Ch. 8.1 to 8.5

RBT: L1, L2, L3

Notes will be uploaded soon

Course Outcomes: The student will be able to :

• Explain fundamentals of image processing
• Compare transformation algorithms
• Contrast enhancement, segmentation, and compression techniques

Question Paper Pattern:

• The question paper will have ten questions.
• Each full Question consisting of 20 marks
• There will be 2 full questions (with a maximum of four sub questions) from each module.
• Each full question will have sub questions covering all the topics under a module.
• The students will have to answer 5 full questions, selecting one full question from each module.

Textbooks:

1. Rafael C G., Woods R E. and Eddins S L, Digital Image Processing, Prentice-Hall, 2nd edition, 2008.

Reference Books:

1. Milan Sonka,” Image Processing, analysis and Machine Vision”, Thomson Press India Ltd, Fourth Edition.
2. Fundamentals of Digital Image Processing- Anil K. Jain, 2nd Edition, Prentice Hall of India.
3. S. Sridhar, Digital Image Processing, Oxford University Press, 2nd Ed, 2016.
4. Digital Image Processing (with Matlab and Labview), Vipul singh, elsiver.Filip learning