Unit I Digital Image Fundamentals 9

DOC/LP/01/28.02.02

LESSON PLAN LP- AP9251 LP Rev. No: 01 SubCode& Name : AP9251 DIGITAL IMAGE PROCESSING Date:24/08/2010 Unit: I Branch: ME-CS Semester: I Page 01 of 06

Unit syllabus:

UNIT I DIGITAL IMAGE FUNDAMENTALS 9

Elements of digital image processing systems, Vidicon and Digital Camera working principles, Elements of visual perception, brightness, contrast, hue, saturation, Mach Band effect, Image sampling, Quantization, Dither, Two dimensional mathematical preliminaries.

Objective: To study the image fundamentals and mathematical transforms necessary for image processing.

Teaching Method Session Topics to be covered Time Ref No 1. Elements of digital image processing systems 50m 1 BB 2. Vidicon and Digital Camera working principles 50m 1,3 OHP 3. Elements of visual perception 50m 1,3 BB 4. Brightness, contrast, hue, saturation, Mach Band effect 50m 1,3 BB 5. Image sampling 50m 1 BB 6. Image quantization 50m 1,3 BB 7. Dither 50m 1 BB Two dimensional mathematical preliminaries. BB 8. 50m 1,3 Two dimensional mathematical preliminaries. BB 9. 50m 1,3 DOC/LP/01/28.02.02

LESSON PLAN LP- AP9251 LP Rev. No: 01 Date: 24/08/2010 SubCode& Name : AP9251 DIGITAL IMAGE PROCESSING Page 02 of 06 Unit: II Branch: ME-CS Semester: I

Unit syllabus:

UNIT II IMAGE TRANSFORMS 9 1D DFT, 2D transforms - DFT, DCT, Discrete Sine, Walsh, Hadamard, Slant, Haar, KLT, SVD, Wavelet transform.

Objective: To study the mathematical transforms necessary for image processing.

Teaching Session Topics to be covered Time Ref Method No 10. Introduction to Fourier Transform and DFT 50m 1.2 BB 11. Properties of 2D Fourier Transform and FFT 50m 1.2 BB Separable Image Transforms –Walsh and Hadamard 50m 1.2 12. BB Transform 13. Discrete Cosine Transform, Haar Transform 50m 1.2 BB 14. Problems 50m 1.2 BB 15. Slant Transform 50m 1.2 BB 16. Karhunen – Loeve transforms 50m 1.2 BB 17. SVD ,Wavelet transform 50m 1.2 BB 18. Problems 50m 1.2 BB 19. CAT-I 90m DOC/LP/01/28.02.02

LESSON PLAN LP- AP9251 LP Rev. No: 01 Date: 24/08/2010 SubCode& Name : AP9251 DIGITAL IMAGE PROCESSING Page 03 of 06 Unit: III Branch: ME-CS Semester: I

Unit syllabus:

UNIT III IMAGE ENHANCEMENT AND RESTORATION 9

Histogram modification, Noise distributions, Spatial averaging, Directional Smoothing, Median, Geometric mean, Harmonic mean, Contraharmonic and Yp mean filters . Design of 2D FIR filters. Image restoration - degradation model, Unconstrained and Constrained restoration, Inverse filtering-removal of blur caused by uniform linear motion, Wiener filtering, Geometric transformations-spatial transformations, Gray Level interpolation. .

Objective: To study image enhancement and restoration procedures.

Session Teaching No Topics to be covered Time Ref with Method page no Image enhancement types,Point operations-contrast BB 20. 50m 1 stretching, clipping and thresholding bit extraction Histogram modeling, equalization, modification and OHP 21. 50m 1,2 specification Spatial averaging ,Directional Smoothing Noise 50m BB 22. 1 models 23. Enhancement using Laplacian and gradical 50m 1 BB 24. Enhancement in frequency domain 50m 1,2 BB 25. Model of Image Degradation/restoration process 50m 1 BB 26. Noise models –Different types of noise 50m 1,2 BB 27. Least mean square filtering , Wiener filtering 50m 1,2 BB Adaptive filter, Unconstrained and Constrained 50m 1 BB 28. restoration Geometric transformations-spatial transformations, 50m OHP 29. 1 Gray Level interpolation DOC/LP/01/28.02.02

LESSON PLAN LP- AP9251 LP Rev. No: 01 Date: 24/08/2010 SubCode& Name : AP9251 DIGITAL IMAGE PROCESSING Page 04 of 06 Unit: IV Branch: ME-CS Semester: I

Unit syllabus:

UNIT IV IMAGE SEGMENTATION AND RECOGNITION 9

Image segmentation - Edge detection, Edge linking and boundary detection, Region growing, Region splitting and Merging, Image Recognition - Patterns and pattern classes, Matching by minimum distance classifier, Matching by correlation.Neural networks- Backpropagation network and training, Neural network to recognize shapes.

Objective: To study the image segmentation and recognition procedures.

Session Teaching No Topics to be covered Time Ref Method 30 Image segmentation- Point and line detection 50m 1,6,7 OHP 31 Edge detection 50m 1,6,7 BB Edge linking-local and global processing, 50m 1,6,7 BB 32 boundary detection 33 Region growing, Region splitting and Merging 50m 1,6,7 BB 34 Image Recognition-Descriptors 50m 1,6,7 OHP 35 Patterns and pattern classes 50m 1,6,7 BB Matching by minimum distance classifier, 50m 1,6,7 BB 36 Matching by correlation Neural networks ,Backpropagation network and 50m OHP 37 1,6,7 training 38 Neural network to recognize shapes 50m 1,6,7 OHP 39 CAT-II 90m DOC/LP/01/28.02.02

LESSON PLAN LP- AP9251 LP Rev. No: 01 Date: 24/08/2010 SubCode& Name : AP9251 DIGITAL IMAGE PROCESSING Page 05 of 06 Unit: V Branch: ME-CS Semester: I

Unit syllabus:

UNIT V IMAGE COMPRESSION 9

Need for data compression, Huffman, Run Length Encoding, Shift codes, Arithmetic coding, Vector Quantization, Block Truncation Coding, Transform coding, JPEG standard, JPEG 2000, EZW, SPIHT, MPEG.

Objective: To study the image compression techniques.

Session Teaching No Topics to be covered Time Ref Method

40. Need for data compression 50m 1 BB 41. Huffman, Run Length Encoding 50m 1,5 BB 42. Shift codes, Arithmetic coding 50m 1,4 BB 43. Block Truncation Coding 50m 1 BB 44. Transform coding 50m 1,5 BB 45. JPEG standard, JPEG 2000 50m 1 OHP 46. EZW,SPIHT 50m 1,5 OHP 47. MPEG 50m 1,5 BB 48. CAT III 90m DOC/LP/01/28.02.02

LESSON PLAN LP- AP9251 LP Rev. No: 01 Date: 24/08/2010 SubCode& Name : AP9251 DIGITAL IMAGE PROCESSING Page 06 of 06 Unit:I-V Branch: ME-CS Semester: I

TEXT BOOKS 1. Rafael C Gonzalez, Richard E Woods 2nd Edition, Digital Image Processing - Pearson Education 2003.

REFERENCES 2. William K Pratt, Digital Image Processing John Willey (2001) 3. Image Processing Analysis and Machine Vision – Millman Sonka, Vaclav hlavac, Roger Boyle, Broos/colic, Thompson Learniy (1999). 4. A.K. Jain, PHI, New Delhi (1995)-Fundamentals of Digital Image Processing. 5. Chanda Dutta Magundar – Digital Image Processing and Applications, Prentice Hall of India, 2000

Course Delivery Plan:

1 2 3 4 5 6 7 8 9 10 11 12 Week I II I II I II I II I II I II I II I II I II I II I II I II 1 2 C 3 4 C 5 C A A A Units T T T I II III

Text Books:

Prepared by Approved by

Signature Name D.MENAKA PROF.E.G.GOVINDAN Designation ASSISTANT PROFESSOR HOD - EC Date 24/08/2010 24/08/2010