SRI VENKATESWARA COLLEGE OF ENGINEERING. COURSE DELIVERY PLAN - THEORY Page 1 of 6

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1 COURSE DELIVERY PLAN - THEORY Page 1 of 6 Department of Electronics and Communication Engineering B.E/B.Tech/M.E/M.Tech : EC Regulation: 2013 PG Specialisation : NA Sub. Code / Sub. Name : IT6005/DIGITAL IMAGE PROCESSING Unit : I LP: IT6005 Rev. No: 00 Date: 28/06/2018 Unit Syllabus: DIGITAL IMAGE FUNDAMENTALS 8 Introduction Origin Steps in Digital Image Processing Components Elements of Visual Perception Image Sensing and Acquisition Image Sampling and Quantization Relationships between pixels - color models. To be familiar with digital image fundamentals. 1. Introduction and Origin of digital image processing systems 1,6 2. Steps in Digital Image Processing and Components 3. Elements of visual perception-structure of Human Eye, Brightness, Adaptation and Discrimination 4. Contrast, hue, saturation, mach band effect 5. Image Sensing and Acquisition 6. Image sampling and quantization, Dither 7. Relationships between pixels-adjacency and Connectivity of pixels 8. Color image fundamentals - RGB, HSI and CMY models Conversion of RGB to HSI and viceversa; Dither 1,3 1,3 1,8 ICT 1,3 /BB 1,6 1,2 * duration: 50 minutes

2 COURSE DELIVERY PLAN - THEORY Page 2 of 6 Unit : II Unit Syllabus: IMAGE ENHANCEMENT 10 Spatial Domain: Gray level transformations Histogram processing Basics of Spatial Filtering Smoothing and Sharpening Spatial Filtering Frequency Domain: Introduction to Fourier Transform Smoothing and Sharpening frequency domain filters Ideal, Butterworth and Gaussian filters. To get exposed with simple image enhancement techniques in Spatial and Frequency domain. 9. Spatial Domain methods: Basic gray level transformation 10. Histogram equalization ; Implementation using MATLAB 11. Histogram specification techniques 12. Basics of Spatial Filtering- Image subtraction and Image averaging CAT-I 13. Smoothing filters; Implementation using MATLAB 14. Sharpening filters-laplacian and Gradient operators Introduction to Frequency domain filtering using Fourier Transform; Basics of 2D Fourier Transform Smoothing frequency domain filters Ideal, Butterworth and Gaussian filters. Sharpening frequency domain filters Ideal, Butterworth and Gaussian filters. 18. Tutorial Implementation of simple image enhancement techniques using MATLAB. 1,2,3, 7 1,2,7 /BB /BB 1,4 1,2,4 1,4 1,3 1,2 /BB * duration: 50 mins

3 COURSE DELIVERY PLAN - THEORY Page 3 of 6 Unit : III Unit Syllabus: IMAGE RESTORATION AND SEGMENTATION 9 Noise models Mean Filters Order Statistics Adaptive filters Band reject Filters Band pass Filters Notch Filters Optimum Notch Filtering Inverse Filtering Wiener filtering Segmentation: Detection of Discontinuities Edge Linking and Boundary detection Region based segmentation; Morphological processing- erosion and dilation. To get exposed with simple Image restoration and Segmentation techniques. 19. Model of Image Degradation/restoration process 1,3,7 20. Noise models; Mean Filters, Order Statistics, Adaptive filters 21. Band reject Filters, Band pass Filters 22. Notch Filters, Optimum Notch Filtering 23. Estimation of degradation function and Inverse filtering, Wiener filtering 24. Introduction to Segmentation, Detection of Discontinuities 25. Edge Linking and Boundary detection 26. Region based segmentation Morphological processing- erosion and dilation; Opening and 27. Closing operation Estimation of degradation function; Opening and Closing operation 1,3 1,3 1,4 1,3,4 1,4 * duration: 50 mins

4 COURSE DELIVERY PLAN - THEORY Page 4 of 6 Unit : IV Unit Syllabus: WAVELETS AND IMAGE COMPRESSION 9 Wavelets Subband coding - Multiresolution expansions - Compression: Fundamentals Image Compression models Error Free Compression Variable Length Coding Bit-Plane Coding Lossless Predictive Coding Lossy Compression Lossy Predictive Coding Compression Standards. To get familiar with image compression methods. 28. Wavelets-Introduction, Continuous and Discrete Wavelet transform 1,2 29. Subband coding; Multiresolution expansions 30. Compression: Need for data compression, Different types of compression; Various types of Redundancy Fundamentals ; Image Compression models CAT-II 31. Error Free Compression 32. Variable Length Coding 33. Bit-Plane Coding 34. Lossless Predictive Coding 35. Lossy Compression Lossy Predictive Coding 36. Compression Standards-JPEG,MPEG Introduction to Information Theory and Types of Redundancy. 1,2 1,2 * duration: 50 mins

5 COURSE DELIVERY PLAN - THEORY Page 5 of 6 Unit : V Unit Syllabus: IMAGE REPRESENTATION AND RECOGNITION 9 Boundary representation Chain Code Polygonal approximation, signature, boundary segments Boundary description Shape number Fourier Descriptor, moments- Regional Descriptors Topological feature, Texture - Patterns and Pattern classes - Recognition based on matching. To represent image in the form of different features. 37. Boundary representation Chain Code, Polygonal approximation 39. Signature, boundary segments 40. Boundary description,shape number 41. Fourier Descriptor, Moments 42. Regional Descriptors 43. Topological feature, Texture 44. Patterns and Pattern classes 1,5 45. Recognition based on matching 1,5 CAT-III Nil * duration: 50 mins

6 COURSE DELIVERY PLAN - THEORY Page 6 of 6 REFERENCES: 1. Rafael C. Gonzales, Richard E. Woods, Digital Image Processing, Third Edition, Pearson Education, Rafael C. Gonzalez, Richard E. Woods, Steven L. Eddins, Digital Image Processing Using MATLAB, Third Edition Tata Mc Graw Hill Pvt. Ltd., Anil Jain K. Fundamentals of Digital Image Processing, PHI Learning Pvt. Ltd., Willliam K Pratt, Digital Image Processing, John Willey, Malay K. Pakhira, Digital Image Processing and Pattern Recognition, First Edition, PHI Learning Pvt. Ltd., Prepared by Approved by Signature /signed/ /signed/ Name L.Anju,D.Menaka Dr.S.Muthukumar Designation Asssistant Professor Prof &HoD/ECE S.P.Sivagnana subramanian, AP Remarks *: The above lesson plan is followed for the academic year Remarks *: * If the same lesson plan is followed in the subsequent semester/year it should be mentioned and signed by the Faculty and the HOD