DOC/LP/00/21.01.05

/ LESSON PLAN / LP- EC2029
LP Rev. No: 00
Date: 06/07/2011
Page 01 of 06
Sub Code& Name : EC2029- DIGITAL IMAGE PROCESSING Unit: I Branch: ECE Semester:VII

UNIT-I DIGITAL IMAGE FUNDAMENTALS AND TRANSFORMS 9

Elements of digital image processing systems, Vidicon and Digital Camera working principles, Elements of visual perception, brightness, contrast, hue, saturation, mach band effect, Color image fundamentals - RGB, HSI models, Image sampling, Quantization, dither, Two-dimensional mathematical preliminaries, 2D transforms -DFT, DCT, KLT, SVD.

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

Session
No / Topics to be covered / Time / Ref / Teaching Method
1.  / Elements of digital image processing systems / 50m / 1 / BB
2.  / Vidicon and Digital Camera working principles / 50m / 2 / OHP
3.  / Elements of visual perception / 50m / 1 / OHP
4.  / Brightness, contrast, hue, saturation, mach band effect / 50m / 1 / BB
5.  / Color image fundamentals - RGB, HSI models / 50m / 1 / BB
6.  / Image sampling and quantization, Dither / 50m / 1 / BB
7.  / Two-dimensional mathematical preliminaries / 50m / 2 / BB
8.  / Two-dimensional mathematical preliminaries / 50m / 2 / BB
9.  / Introduction to Fourier Transform and DFT / 50m / 2,4 / BB
10.  / Discrete Cosine Transform and its properties / 50m / 2,4 / BB
11.  / Karhunen – Loeve transforms and its properties / 50m / 2 / BB
12.  / Singular Value Decomposition and its properties / 50m / 2 / BB
CAT 1 / 50m
/ LESSON PLAN / LP- EC2029
LP Rev. No: 00
Date: 06/07/2011
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Sub Code& Name : EC2029- DIGITAL IMAGE PROCESSING Unit: II Branch: ECE Semester:VII

UNIT II IMAGE ENHANCEMENT 9

Histogram equalization and specification techniques, Noise distributions, Spatial averaging, Directional Smoothing, Median, Geometric mean, Harmonic mean, Contraharmonic mean filters, Homomorphic filtering, Color image enhancement.

Objective: To study the image enhancement techniques

Session
No / Topics to be covered / Time / Ref / Teaching Method
13.  / Spatial Domain methods: Basic grey level transformation / 50m / 1,4 / BB
14.  / Histogram equalization Histogram specification techniques / 50m / 1,4 / BB
15.  / Noise Distributions / 50m / 1,4 / BB
16.  / Image subtraction and Image averaging / 50m / 1 / BB
17.  / Smoothing, sharpening filters / 50m / 1,4 / BB
18.  / Geometric mean, Harmonic mean, Contraharmonic mean filters / 50m / 1 / BB
19.  / Homomorphic filtering / 50m / 1 / BB
20.  / Color image enhancement techniques / 50m / 1 / BB
21.  / Color image enhancement techniques / 50m / 1,4 / PPT
CAT-II / 50m
/ LESSON PLAN / LP- EC2029
LP Rev. No: 00
Date: 06/07/2011
Page 03 of 06
Sub Code& Name : EC2029-DIGITAL IMAGE PROCESSING Unit: III Branch: ECE Semester:VII

UNIT III IMAGE RESTORATION 9

Image Restoration - degradation model, Unconstrained restoration - Lagrange multiplier and Constrained restoration, Inverse filtering-removal of blur caused by uniform linear motion, Wiener filtering, Geometric transformations-spatial transformation.

Objective: To study image restoration procedures.

Session
No / Topics to be covered / Time / Ref / Teaching Method
22.  / Model of Image Degradation/restoration process / 50m / 1 / BB
23.  / Noise models / 50m / 1 / BB
24.  / Unconstrained restoration / 50m / 1 / BB
25.  / Lagrange multiplier / 50m / 1 / BB
26.  / Least mean square filtering / 50m / 1,4 / BB
27.  / Constrained least mean square filtering / 50m / 1,3 / BB
28.  / Inverse filtering-removal of blur caused by uniform linear motion / 50m / 1 / BB
29.  / Wiener filtering / 50m / 1,4 / BB
30.  / Geometric transformations / 50m / 1 / BB
31.  / Spatial transformation / 50m / 1 / BB
CAT-III / 50m
/ LESSON PLAN / LP- EC2029
LP Rev. No: 00
Date: 06/07/2011
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Sub Code& Name : EC2029- DIGITAL IMAGE PROCESSING Unit: V Branch: ECE Semester:VII

UNIT V IMAGE COMPRESSION 9

Need for data compression, Huffman, Run Length Encoding, Shift codes, Arithmetic coding, Vector Quantization, Transform coding, JPEG standard, MPEG.

Objective: To study the image compression techniques.

Session
No / Topics to be covered / Time / Ref / Teaching Method
32.  / Need for data compression, Different types of compression / 50m / 6 / BB
33.  / Variable length coding-Huffman Coding / 50m / 1,3 / BB
34.  / Tutorials / 50m / 1,3 / BB
35.  / Run Length Encoding, Shift codes / 50m / 1 / BB
36.  / Arithmetic coding / 50m / 4 / BB
37.  / Vector Quantization / 50m / 4 / BB
38.  / Lossy Compression: Transform coding / 50m / 1,4 / BB
39.  / Wavelet coding / 50m / 1,4 / BB
40.  / Basics of Image compression standards: JPEG / 50m / 1 / PPT
41.  / MPEG standards / 50m / 1 / PPT
CAT-IV / 50m
/ LESSON PLAN / LP- EC2029
LP Rev. No: 00
Date: 06/07/2011
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Sub Code& Name : EC2029-DIGITAL IMAGE PROCESSING Unit: IV Branch: ECE Semester:VII

UNIT IV IMAGE SEGMENTATION 9

Edge detection, Edge linking via Hough transform – Thresholding - Region based segmentation – Region growing – Region splitting and Merging – Segmentation by morphological watersheds – basic concepts – Dam construction – Watershed segmentation algorithm.

Objective: To study the image segmentation procedures.

Session
No / Topics to be covered / Time / Ref / Teaching Method
42.  / Edge detection / 50m / 1 / BB
43.  / Edge linking via Hough transform / 50m / 1 / BB
44.  / Thresholding / 50m / 1 / BB
45.  / Region Based segmentation / 50m / 1,4 / BB
46.  / Region growing / 50m / 1 / BB
47.  / Region splitting and Merging / 50m / 1 / BB
48.  / Segmentation by morphological watersheds – basic concepts / 50m / 1,7 / PPT
49.  / Dam construction / 50m / 1,7 / PPT
50.  / Watershed segmentation algorithm / 50m / 1,7 / PPT
CAT-V / 50m
/ LESSON PLAN / LP- EC2029
LP Rev. No: 00
Date: 06/07/2011
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SubCode& Name : EC2029-DIGITAL IMAGE PROCESSING Branch: ECE Semester:VII

Course Delivery Plan:

Week / 1 / 2 / 3 / 4 / 5 / 6 / 7 / 8 / 9 / 10 / 11 / 12 / 13 / 14 / 15
I II / I II / I II / I II / I II / I II / I II / I II / I II / I II / I II / I II / I II / I II / I II
Units / / 1 / / 2 / / 3 / / 5 / / / 4 /

TEXTBOOKS:

1. Rafael C. Gonzalez, Richard E. Woods, , “Digital Image Processing”, Pearson ,Second Edition, 2004.

2. Anil K. Jain, “Fundamentals of Digital Image Processing”, Pearson 2002.

REFERENCES:

3. Kenneth R. Castleman, “Digital Image Processing”, Pearson, 2006.

4. Rafael C. Gonzalez, Richard E. Woods, Steven Eddins,” Digital Image Processing using

MATLAB”, Pearson Education, Inc., 2004.

5. D,E. Dudgeon and RM. Mersereau, , Multidimensional Digital Signal Processing',Prentice Hall

Professional Technical Reference, 1990.

6. William K. Pratt, , Digital Image Processing' , John Wiley, New York, 2002.

7. Milan Sonka et aI, 'Image Processing, Analysis And Machine Vision', Brookes/Cole, Vikas

Publishing House, 2nd edition, 1999.

Prepared by / Approved by

Signature

Name / Ms.L.ANJU, Ms.D.MENAKA / PROF.E.G.GOVINDAN
Designation / ASSISTANT PROFESSOR / HOD-EC
Date / 06/07/2011 / 06/07/2011