DSIP (Digital Signal and Image Processing)

Description
What you’ll Learn:
 Digital Signal
Digital signal processing fundamentals and the numerical.
The fundamental concepts on Fourier Transforms
Root concepts like signals, noise, convolution, quantization, sampling. and many more
Complex concepts and their numerical like FFT, DITFFT made easy for you.
 Image Processing
Starting from basic 2D images and getting into complex processing algorithms.
Numerical based on image segmentation, Histogram , Grey level & Zero memory point operations.Digital Signal processing has a vast background comprising of signals, their fundamental properties, and their applications in the real world. This course offers tutorials on the subject as a whole with inline explanation and handy .pdf notes.
Images being the easiest way of getting information across, starting from artistic to marketing. And today, images are digital. So, it's important to know about image processing tasks including image enhancement, filtering, and image compression which are covered thoroughly.
Along with a pdf with important notes and explanations
Modules Covered:
DiscreteTime Signal /System
Discrete Fourier Transform
Fast Fourier Transform
Digital Image fundamentals
Image Enhancement
Image Segmentation 
How to Pass DSIP

DiscreteTime Signal and DiscreteTime System
 Introduction to Digital Signal Processing
 Determine signal is periodic or aperiodic
 Determine signal is linear or nonlinear
 Determine Signal is Time varient or Invarient
 Determine Signal is Static or Dynamic
 Determine Signal is Causal or Non Causal
 Determine Signal is Stable and unstable
 Find Linear Convolution part 1
 Find Linear Convolution part 2
 Circular Convolution
 Cross Correlation and Auto Correlation
 Energy and Power Signal
 Types of Signals
 Stability Sum (find the range of linear time invariant signal for which impulse response is stable)
 Output response (0.3 delta wala sum )

Discrete Fourier Transform

Fast Fourier Transform

Doubt Solving Session

Digital Image Fundamentals

Image Enhancement in Spatial domain

Image Segmentation

Image Processing New Video

Digital Signal Processing Notes

Image Processing Notes

DSIP Notes
DSIP (Digital Signal and Image Processing)
Tutor: Sumersingh Rajpurohit
What you’ll Learn:
– Digital Signal
Digital signal processing fundamentals and the numerical.
The fundamental concepts on Fourier Transforms
Root concepts like signals, noise, convolution, quantization, sampling. and many more
Complex concepts and their numerical like FFT, DITFFT made easy for you.
– Image Processing
Starting from basic 2D images and getting into complex processing algorithms.
Numerical based on image segmentation, Histogram , Grey level & Zero memory point operations.
Description:
Digital Signal & Image Processing is semester 7 subject of final year of computer engineering in Mumbai University. Prerequisite for studying this subject are Applied Mathematics. Course objectives for subject Digital Signal & Image Processing is to understand the fundamental concepts of digital signal processing and Image processing. To explore DFT for 1D and 2D signal and FFT for 1D signal. To apply processing techniques on 1D and Image signals. To apply digital image processing techniques for edge detection. Course outcomes for subject Digital Signal & Image Processing On successful completion of the course learner will be able to: Apply the concept of DT Signal and DT Systems. Classify and analyze discrete time signals and systems. Implement Digital Signal Transform technique DFT and FFT. Use the enhancement techniques for digital Image Processing. Differentiate between the advantages and disadvantages of different edge detection techniques. Develop small projects of 1D and 2D Digital Signal Processing.
A digital signal is a signal that is being used to represent data as a sequence of discrete values; at any given time it can only take on, at most, one of a finite number of values. This contrasts with an analog signal, which represents continuous values; at any given time it represents a real number within a continuous range of values. Digital image processing is the use of a digital computer to process digital images through an algorithm. As a subcategory or field of digital signal processing, digital image processing has many advantages over analog image processing. It allows a much wider range of algorithms to be applied to the input data and can avoid problems such as the buildup of noise and distortion during processing. Since images are defined over two dimensions digital image processing may be modeled in the form of multidimensional systems. The generation and development of digital image processing are mainly affected by three factors: first, the development of computers; second, the development of mathematics; third, the demand for a wide range of applications in environment, agriculture, military, industry and medical science has increased.
Module DiscreteTime Signal and DiscreteTime System consists of the following subtopics such as Introduction to Digital Signal Processing, Sampling and Reconstruction, Standard DT Signals, Concept of Digital Frequency, Representation of DT signal using Standard DT Signals, Signal Manipulations (shifting, reversal, scaling, addition, multiplication). Classification of DiscreteTime Signals, Classification of Discrete Systems. Linear Convolution formulation for 1D and 2D signal (without mathematical proof), Circular Convolution (without mathematical proof), Linear convolution using Circular Convolution. Auto and Cross Correlation formula evaluation, LTI system, Concept of Impulse Response and Step Response, Output of DT system using Time Domain Linear Convolution.
Module Discrete Fourier Transform consists of the following subtopics such as Introduction to DTFT, DFT, Relation between DFT and DTFT, IDF.T Properties of DFT without mathematical proof (Scaling and Linearity, Periodicity, Time Shift and Frequency Shift, Time Reversal, Convolution Property and Parsevals‘ Energy Theorem). DFT computation using DFT properties. Transfer function of DT System in frequency domain using DFT. Linear and Circular Convolution using DFT, Convolution of long sequences, Introduction to 2D DFT. Module Fast Fourier Transform consists of the following subtopics such as Need of FFT, Radix2 DITFFT algorithm, DITFFT Flow graph for N=4 and 8, Inverse FFT algorithm. Spectral Analysis using FFT. Module Digital Image Fundamentals consists of the following subtopics such as Introduction to Digital Image, Digital Image Processing System, Sampling and Quantization. Representation of Digital Image, Connectivity. Image File Formats: BMP, TIFF and JPEG. Module Image Enhancement in Spatial domain consists of the following subtopics such as Gray Level Transformations, Zero Memory Point Operations, Histogram Processing, Histogram equalization. Neighborhood Processing, Spatial Filtering, Smoothing and Sharpening Filters, Median Filter. Module Image Segmentation consists of the following subtopics such as Segmentation based on Discontinuities (point, Line, Edge), Image Edge detection using Robert, Sobel, Previtt masks, Image Edge detection using Laplacian Mask.
Suggested Texts Books for the subject Digital Signal & Image Processing by Mumbai University is as follows John G. Proakis, Dimitris and G.Manolakis, Digital Signal Processing: Principles, Algorithms, and Applications‘4th Edition 2007, Pearson Education. A. Anand Kumar, Digital Signal Processing, PHI Learning Pvt. Ltd. 2013. Rafel C. Gonzalez and Richard E. Woods, Digital Image Processing, Pearson Education Asia, 3rd Edition, 2009, S. Sridhar, Digital Image Processing‘, Oxford University Press, Second Edition, 2012. Suggested Reference Books for the subject Digital Signal & Image Processing by Mumbai university is as follows Sanjit Mitra, Digital Signal Processing: A Computer Based Approach‘, TataMcGraw Hill, 3rd Edition. S. Salivahanan, A. Vallavaraj, and C. Gnanapriya, ‗Digital Signal Processing‘ Tata McGraw Hill Publication 1st Edition (2010). S. Jayaraman, E. Esakkirajan and T. Veerkumar, Digital Image Processing‘ TataMcGraw Hill Education Private Ltd, 2009. Anil K. Jain, Fundamentals and Digital Image Processing‘, Prentice Hall of India Private Ltd, 3rd Edition.
Join in to learn Digital Signal and Image processing fundamentals, equally important from the academic as well as realworld knowledge.
Modules Covered:
DiscreteTime Signal /System
Discrete Fourier Transform
Fast Fourier Transform
Digital Image fundamentals
Image Enhancement
Image Segmentation
Feel forward to have a look at course description and demo videos and we look forward to see you learning with us.
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Course Features
 Lectures 47
 Quizzes 0
 Duration 50 hours
 Skill level All levels
 Language English
 Students 120
 Certificate No
 Assessments Yes

Rohan
Worth taking
Tysm sumer...... Was a very helpful course