Digital Signal & Image Processing
Teacher
Debaraj Rana
Category
Core Courses
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Course Name : Digital Signal & Image Processing
Code(Credit) : CUTM1048(2-1-0)
Course Objectives
- To teach students time domain,frequency domain,discrete time signals, properties and digital filter design techniques
- To provide knowledge on basic concepts of image and its processing techniques
- To provide knowledge on Enhancement, Restoration, Segmentation techniques
- To provide hand on experience of signal & image processing techniques using MATLAB
Course Outcome
| COs | Course outcomes | Mapping COs with POs (High-3, Medium-2, Low-1) |
| CO1 | Students will gain knowledge on fundamental concepts of a digital signal and image processing System | PO1(3) |
| CO2 | Analytical and critical thinking of Signal and Image processing algorithms. | PO2(3) |
| CO3 | Students will develop skill of developing new algorithms in signal and image processing Applications. | PO2(3), PO3 (3) |
| CO4 | Student will develop skill on MATLAB implementation of different signal and image processing techniques. | PO4(2), PO5 (3) |
Course Syllabus
Module I: FUNDAMENTALS OF DIGITAL SIGNAL PROCESSING (3 Hrs)
Characterization and classification of signals, Z-Transform: Direct Z-Transform, inverse Z-Transform, Properties of The ZTransform, Linearity, Time Shifting, Scaling, Time Reversal, Differentiation, Convolution, Correlation, Accumulation, System Function of a Linear Time-Invariant System
Practice:
- Signal generation using MATLAB.
- Analysis of LTI system and Z-transform of signal using MATLAB.
Module II: DISCRETE FOURIER TRANSFORM & FAST FOURIER TRANSFORM (4 Hrs)
DTFT and DFT Relationship, Discrete Fourier transform (DFT), Properties of the DFT: periodicity, linearity, and symmetry properties, relationship of the DFT to other transforms, DFT as a linear transformation, multiplication of two DFT and circular convolution, Efficient Computation of the DFT, FFT Algorithms: Radix-2 FFT Algorithms: Decimation in-Time (DIT), Decimation-in-Frequency (DIF)
Practice:
- MATLAB simulation for DFT & IDFT.
- DIT and DIF FFT by MATLAB simulation.
Module III: DESIGN AND REALIZATION OF DIGITAL FIR FILTERS (5 Hrs)
FIR Filter Structure: Direct Form-I, Direct Form-II, Linear Phase FIR Filter, Liner Phase FIR Filter, Design of FIR Filters Using Windowing Techniques, Design of FIR Filter by Frequency Sampling Technique
Practice:
- MATLAB Simulation of FIR filters using windows technique (Rectangular, Hamming and Hanning).
- MATLAB simulation of LPF and high pass filter by FIR filter.
Module IV: DESIGN AND REALIZATION OF DIGITAL IIR FILTERS (4 Hrs)
Design of IIR Filters from Analog Filters(Butterworth Approximation): IIR Filter Design by Impulse Invariance, IIR Filter Design By The Bilinear Transformation, Realization of Digital Filter by using Direct Form-I, Direct Form-II, Cascade Form and Parallel Form Structures.
Practice:
- Design of IIR Butterworth filter from filter specification (both programming & and by using FDA tool box).
- Design of IIR low pass Butterworth filter using impulse invariant transformation from filter specification.
Module V: DIGITAL IMAGE FUNDAMENTAL (4 Hrs)
Image fundamental, Types of Images, A simple Image Model, Steps of Image Processing, Color Image and Color Models, Sampling and Quantization, Pixel Relationship (Neighbor and Adjacency)
Practice:
- Image read and writes operation using MATLAB.
- Reading an image and display the grayscale, color and B/W image using MATLAB.
- Reading an RGB Image and extract the color components using MATLAB.
Module VI: DIGITAL IMAGE ENHANCEMENT (5 Hrs)
Spatial Domain Enhancement, Brightness and Contrast Enhancement, , Basic Gray Level Enhancement-Image Negative, Histogram Equalization, Basic Filtering Operation for Smoothing and Sharpening Filter (Use of Filter Kernel), 2D Fourier Transform and Filtering in Frequency Domain, Ideal Low pass and High Pass Filter for Frequency domain Smoothing and Sharpening
Practice:
- Brightness and contrast enhancement of an image using MATLAB.
- Simulation of Image negative using MATLAB.
- MATLAB Simulation of Image smoothing and sharpening using different mask.
Module VII: DIGITAL IMAGE RESTORATION (4 Hrs)
Image Restoration, Model of Image Degradation / Restoration process, Gaussian and Salt and Pepper Noise, Restoration using Mean Filters and Order Statistic Filters (Median and Min-Max Filtering)
Practice:
- MATLAB Simulation of Image noising using different noise distribution.
- MATLAB Simulation of Image De-noising using Arithmetic mean and median filter.
- MATLAB Simulation of Image De-noising using Order Statistics Filter (Median, Min-Max Filter).
Text Books :
- V. K. Ingle and J.G. Proaksis, J.G, “Digital Signal Processing-A MATLAB Based Approach”, Cengage Learning Publisher
- S. Salivahanan, A. Vallavaraj and C. Gnanapriya, “Digital Signal Processing”, McGraw-Hill Publication
- Gonzalez, Rafael C., and Richard E. Woods, “Digital Image Processing” 2nd Edition, Pearson Education, 2002.
Reference Books :
- Tarun K.Rawat, “Digital Signal Processing”, Oxford University Press India
- Sridhar S. Oxford university publication. Digital Image Processing. 2001.
- Gonzalez, Rafael C., and Richard E. Woods, Steven L Eddins “Digital Image Processing using MATLAB” , Pearson Education, 2009.
- https://sites.google.com/site/mdotarif/teaching/dsip
Session Plan
Session 2
DFT, relationship of the DFT to other transforms (DIF)
https://www.youtube.com/watch?v=spUNpyF58BY
Session 3
Properties of the DFT: Periodicity
problems on Properties of the DFT: Periodicity
Session 4
Efficient Computation of the DFT, FFT Algorithms: Radix-2 FFT Algorithms: Decimation in-Time (DIT), Decimation-in-Frequency
Session 5
FIR Filter Structure, FFT Algorithms, Efficient Computation of the DFT, problems on FFT Algorithms: Direct Computation of the DFT
Session 6
Design of FIR Filters: Symmetric and Ant symmetric FIR Filters, Design of Linear-Phase FIR Filters by using Windows & Frequency Sampling Method
Session 7
Realization of FIR Filter: recursive and non-recursive structure, FIR filter structure: Direct form-I, Direct form-II, Linear phase structure, frequency sampling
structure.
Session 8
Structure for IIR Systems: Direct Form Structures, Cascade- FormStructures, Parallel-Form Structures
Session 9
Design of IIR Filters: Design byImpulse Invariance method
Session 10
IIR Filter Design using Bilinear Transformation techniques, Realization of Digital Filter by using Direct Form-I, Direct Form-II, Cascade Form and Parallel Form Structures.
Session 11
Digital Image fundamental, Types of Images, A simple Image Model
Session 12
Steps of Image Processing, Practice: Image read and writes operation using MATLAB
Session 13
Color Image and Color Models, Practice: Reading an image and display the grayscale, color and B/W image using MATLAB
Session 14
Sampling and Quantization, Pixel Relationship (Neighbor and Adjacency)
https://www.youtube.com/watch?v=MuQUXPoxPXk
Session 15
Practice: Reading an RGB Image and extract the color components using MATLAB
Session 16
Spatial Domain Enhancement, Brightness and Contrast Enhancement, Basic Gray Level Enhancement-Image Negative
Session 17
Practice: MATLAB Simulation of Brightness and contrast enhancement of an image, Simulation of Image negative
Session 18
Histogram Equalization, Practice: MATLAB simulation of Histogram equalization
Session 19
Basic Filtering Operation for Smoothing and Sharpening Filter (Use of Filter Kernel), Practice: MATLAB Simulation of Image smoothing and sharpening using different mask
https://www.youtube.com/watch?v=gFELyrIx010
https://www.youtube.com/watch?v=ZoaEDbivmOE&t=128s
https://www.youtube.com/watch?v=-dRZ1Mv3xMQ&list=PLHLtQZu3roXhE4JrGja1soerwkZlFjERH&index=7
Session 20
Image Enhancement in Frequency Domain, Idea Low pass and high pass filter for Image Smoothing and Sharpening Operation
Session 21
Image Restoration, Model of Image Degradation / Restoration process, Gaussian and Salt and Pepper Noise
Session 22
Restoration using Mean Filters, Practice: MATLAB Simulation of Image noising using different noise distribution
Session 23
Restoration using Order Statistic Filters (Median and Min-Max Filtering), Practice: MATLAB Simulation of Image De-noising
Our Main Teachers
Mr. Debaraj Rana , working as Asst. Professor in the Dept of Electronics & Communication Engineering, School of Engineering and Technology, Bhubaneswar Campus. He has nine years of teaching experience in the field of Electronics and Communication. He has completed his B.Tech from Biju Pattnaik University of Technology and completed in the year 2007 and […]