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Artificial Intelligence of Sharif University of Technology    

    

    Digital Image Processing (DIP):

          By: Dr. M. Jamzad

References:
   

  • Main Text book: Digital Image Processing (2nd Edition)
                                 Authors: Rafael C.Gonzalez, Richard E.Woods
                                  Publisher: Prentice Hall, 2002

  • Supporting Text Book: Digital Image Processing using MATHLAB
                                           Authors: Rafael C.Gonzalez, Richard E.Woods, Steven L.Eddins
                                            Publisher: Prentice Hall, 2004
     
Course syllabus:
     
  1. Introduction
                1.1 What id Digital Image Processing The Origins of digital Image Processing
                1.2 Examples of Fields that Use Digital Image Processing
                1.3 Fundamental Steps in Digital Image Processing
                1.4 Components of Image Processing System

  1. Digital Image Fundamentals
               2.1. Elements of Visual Perception>
               2.2 Light and the Electromagnetic Spectrum
               2.3 Image Sensing and Acquisition
               2.4 Image Sampling and Quantization
               2.5 Some Basic Relationship Between Pixels
               2.6 Linear and Non-Linear Operations

  1. Image Enhancement in the Spatial Domain
               3.1 Background
               3.2 Some Basic Gray Level Transformations
               3.3 Histogram Processing
               3.4 Enhancement Using Arithmetic/Logic Operation
               3.5 Smoothing Spatial Filters
               3.7 Sharpening Spatial Filters
               3.8 Combining Spatial Enhancement Methods

  1. Image Enhancement in the Frequency Domain
               4.1 Background
               4.2 Introduction to Fourier Transform and the Frequency Domain
               4.3 Smoothing Frequency-Domain Filters
               4.4 Sharpening Frequency Domain Filters
               4.5 Homomorphic Filters
               4.6 Implementations
               4. Convolution and Correlation
               4.8 Fast Fourier Transform
               4.9 Walsh, Harr and Discrete Fourier Transform

  1. Image Restoration
               5.1 A Model of the Image Degradation/Restoration Process
               5.2 Noise Models
               5.3 Restoration in the Presence of Noise Only-Spatial Filtering
               5.4 Periodic Noise Reduction by Frequency Domain Filtering
               5.5 Linear, Position-Invariant Degradation
               5.6 Estimating the Degradation Function
               5.7 Inverse Filtering
               5.8 Minimum Mean Square Error (Wiener) Filtering
               5.9 Constrained Least Squares Filtering
               5.10 Geometric Mean Filter
               5.11 Geometric Transformations

  1. Color Image Processing
               6.1 Color Fundamentals
               6.2 Color Models
               6.3 Pseudo color Image Processing
               6.4 Basics of Full-Color Image Processing
               6.5 Color Transforms
               6.6 Smoothing and Sharpening
               6.7 Color Segmentation
               6.8 Noise in Color Images
               6.9 Color Image Compression
     
Course Evaluation is done as follows:
   

  1.  Mid Term Exam

  2.  Final Exam

  3.  Seminar (Oral presentation of a research paper by students)

  4.  Course work (Implementation of some basic algorithms using MATHLAB)

  5. Course Project (Programming a research topic that may be related to the seminar)
     

 
 

 

 

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