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EASWARI ENGINEERING COLLEGE,

RAMAPURAM

Department of Electronics and Communication EngineeringLESSON PLAN

SUBJECT: DIGITAL IMAGE PROCESSING SUBJECTCODE: EC2029

FACULTY NAME: C. AISHWARYA CLASS: IV Year ECEAAIM

To introduce the student to various image processing techniques.OBJECTIVES

To study the image fundamentals and mathematical transforms necessary for

image processing.

To study the image enhancement techniques.

To study image restoration procedures.

To study the image compression procedures.

To study the image segmentation procedures.

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, Color image fundamentals - RGB, HSI models, Image sampling,

Quantization, dither, Two-dimensional mathematical preliminaries, 2D transforms -DFT, DCT, KLT, SVD.

UNIT II IMAGE ENHANCEMENT 9

Histogram equalization and specification techniques, Noise distributions, Spatialaveraging, Directional Smoothing, Median, Geometric mean, Harmonic mean,

Contra harmonic mean filters, Homomorphic filtering, Color image enhancement.

UNIT III IMAGE RESTORATION 9Image 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 transformations.

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 Watershedsegmentation algorithm.

UNIT V IMAGE COMPRESSION 9

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

TOTAL= 45 PERIODS

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:

1. Kenneth R. Castleman, Digital Image Processing, Pearson, 2006.

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2. Rafael C. Gonzalez, Richard E. Woods, Steven Eddins,' Digital Image Processing

using MATLAB', Pearson Education, Inc., 2004.

3. D,E. Dudgeon and RM. Mersereau, , Multidimensional Digital Signal Processing',Prentice Hall Professional Technical Reference, 1990.

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

5. Milan Sonka et aI, 'IMAGE PROCESSING, ANALYSIS AND MACHINEVISION', Brookes/Cole, Vikas Publishing House, 2nd edition, 1999,

6. Jeyaraman, Esakki raja, Digital image processing, TATA Mcgraw Hill .2009

SL.NO DATE PERIOD TOPIC UNIT PAGE NO

1. DIGITAL IMAGE

FUNDAMENTALS Elements

of digital image processing

systems

I T1-28R6-22

2. Vidicon and Digital Camera

working principles

I R6-32,34

3. Elements of visual perception I T1-344. Brightness, contrast, hue,

saturation. Mach

band effect

I T1-40-41

T2-49

5. Color image fundamentals -

RGB

I T1-283

6. HSI models I T1-295

7. Image sampling,Quantization, Dither

I T2-84T2-99, 120

8. Two-dimensionalmathematical preliminaries

I T2-132

9. 2D transforms -DFT ,DCT I T2-145,15010. KLT, SVD I T2-163,R6-

11. IMAGE ENHANCEMENTHistogram equalization and

specification techniques

II T1-88-102

12. Noise distributions II T1-222

13. Spatial averaging II T1-116

14. Directional Smoothing II

15. Median, Geometric mean, II T1-232

16. Harmonic mean,

Contraharmonic mean filters

II T1-231

17. Homomorphic filtering II T1-19118. Color image enhancement. II T1-327

19. IMAGE RESTORATIONImage Restoration

III T1-220

20. Degradation model III T1-221

21. Unconstrained restoration III T1-266

22. Lagrange multiplier III

23. Constrained restoration III T1-266

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24. Inverse filtering-Removal of

blur caused by uniform linearmotion

III T1-261

25. Wiener filtering III T1-262

26. Geometric transformations III T1-270

27. Spatial transformations III T1-27128. IMAGE SEGMENTATION

Edge detectionIV T1-567,572

29. Edge linking via Hough

transform

IV T1-585

30. Thresholding IV T1-595

31. Region based segmentation

Region growing

IV T1-612

32. Region splitting and Merging IV T1-615

33. Segmentation bymorphological watersheds-

basic concepts

IV T1-617

34. Dam construction IV T1-620

35. Watershed Segmentation

algorithm.

IV T1-622

36. IMAGE COMPRESSIONNeed for data compression

V T1-411

37. Huffman coding V T1-441

38. Run Length Encoding V R6-449

39. Shift codes V T1-444

40. Arithmetic coding V T1-444

41. Vector Quantization V R6-497

42. Transform coding V R6-48743. JPEG standard V R6-488

44. MPEG V T1-510

STAFF INCHARGE HOD/ECE

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