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File: Processing Pdf 179025 | Digital Image Processing Vijaya Raghavan
digital image processing scsvmv dept of ece digital image processing lecture notes b e ivyear prepared by dr s vijayaraghavan assistant professor ece scsvmv deemed university kanchipuram page 1 digital ...

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            Digital Image Processing                      SCSVMV                                      Dept of ECE 
             
             
             
             
             
                                                                
                                                                
                  DIGITAL IMAGE PROCESSING 
                                          LECTURE NOTES 
                                                B.E (IVYEAR) 
                                                                
                                                    Prepared by 
                                        Dr.S.Vijayaraghavan 
                                            Assistant Professor-ECE 
                             SCSVMV Deemed University, Kanchipuram 
             
             
             
             
             
             
             
             
             
             
             
             
             
            Page | 1 
             
            Digital Image Processing                      SCSVMV                                      Dept of ECE 
                                              
             
             
                                         DIGITAL IMAGE PROCESSING                             VII-Semester 
              
                 Pre-requisite:  Basic  knowledge of  Signals &                               L   T  P  C 
                Systems, Digital Signal Processing and Digital                                4   1  0   4 
                Design                                                                         
                OBJECTIVES: 
                    ➢  To learn digital image fundamentals. 
                    ➢  To be exposed to simple image processing techniques. 
                    ➢  To  be  familiar  with  image  compression  and  segmentation 
                       techniques 
                    ➢  To represent image in form of features. 
              
                UNIT - I DIGITAL IMAGE FUNDAMENTALS 
                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. 
                UNIT - II IMAGE ENHANCEMENT 
                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. 
                UNIT - III IMAGE RESTORATION AND SEGMENTATION 
                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. 
                 
            Page | 2 
             
            Digital Image Processing                      SCSVMV                                      Dept of ECE 
                UNIT - IV WAVELETS AND IMAGE COMPRESSION 
                Wavelets – Sub band coding – Multi-resolution 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. 
                UNIT - V IMAGE REPRESENTATION AND RECOGNITION 
                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. 
                OUTCOMES: 
                        At the end of the course, the student should be able to: 
                    ✓  Understand the image enhancement techniques 
                    ✓  Understand the concept of restoration and segmentation  
                    ✓  Understand wavelets and image compression 
              
                 
                TEXT BOOK: 
                   1.  Rafael  C.  Gonzales,  Richard  E.  Woods,  “Digital  Image 
                   Processing”, Third Edition, Pearson Education, 2010. 
                 
                REFERENCES: 
                1.  Rafael C. Gonzalez, Richard E. Woods, Steven L. Eddins, “Digital 
                   Image Processing Using MATLAB”, Third Edition Tata Mc Graw 
                   Hill Pvt. Ltd., 2011. 
                2.  Anil Jain K. “Fundamentals of Digital Image Processing”, PHI      
                   Learning Pvt. Ltd., 2011. 
                3.  Willliam K Pratt, “Digital Image Processing”, John Willey, 2002. 
                4.  Malay K. Pakhira, “Digital Image Processing and 
                   Pattern Recognition”, First Edition, PHI Learning 
                   Pvt. Ltd., 2011 
             
            Page | 3 
             
            Digital Image Processing                      SCSVMV                                      Dept of ECE 
             
             
                                                     UNIT-1 
               DIGITAL IMAGE FUNDAMENTALS 
             
            LEARNING OBJECTIVES: 
            This  unit  provides  an  overview  of  the  image  –processing  system  which 
            includes various elements like image sampling, quantization, Basic steps 
            in  image  processing,  image  formation,  storage  and  display.  After 
            completing  this  unit,  the  reader  is  expected  to  be  familiar  with  the 
            following concepts: 
        1. Image sampling 
        2. Image sensors  
        3. Different steps in image processing 
        4. Image formation 
             
            DIGITAL IMAGE FUNDAMENTALS: 
            The field of digital image processing refers to processing digital images by 
            means of digital computer. Digital image is composed of a finite number of 
            elements,  each  of  which  has  a  particular  location  and  value.  These 
            elements  are  called  picture  elements,  image  elements,  pels  and  pixels. 
            Pixel is the term used most widely to denote the elements of digitalimage.  
             
            An image is a two-dimensional function that represents a measure of some 
            characteristic such as brightness or color of a viewed scene. An image is a 
            projection of a 3- D scene into a 2D projection plane. 
             
            Page | 4 
             
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...Digital image processing scsvmv dept of ece lecture notes b e ivyear prepared by dr s vijayaraghavan assistant professor deemed university kanchipuram page vii semester pre requisite basic knowledge signals l t p c systems signal and design objectives to learn fundamentals be exposed simple techniques familiar with compression segmentation represent in form features unit i introduction origin steps components elements visual perception sensing acquisition sampling quantization relationships between pixels color models ii enhancement spatial domain gray level transformations histogram basics filtering smoothing sharpening frequency fourier transform filters ideal butterworth gaussian iii restoration noise mean order statistics adaptive band reject pass notch optimum inverse wiener detection discontinuities edge linking boundary region based morphological erosion dilation iv wavelets sub coding multi resolution expansions error free variable length bit plane lossless predictive lossy sta...

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