
Description 1
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
Lecture1.1


How to Pass DSIP 1

Lecture2.1


DiscreteTime Signal and DiscreteTime System 15

Lecture3.1

Lecture3.2

Lecture3.3

Lecture3.4

Lecture3.5

Lecture3.6

Lecture3.7

Lecture3.8

Lecture3.9

Lecture3.10

Lecture3.11

Lecture3.12

Lecture3.13

Lecture3.14

Lecture3.15


Discrete Fourier Transform 5

Lecture4.1

Lecture4.2

Lecture4.3

Lecture4.4

Lecture4.5


Fast Fourier Transform 1

Lecture5.1


Doubt Solving Session 1

Lecture6.1


Digital Image Fundamentals 5

Lecture7.1

Lecture7.2

Lecture7.3

Lecture7.4

Lecture7.5


Image Enhancement in Spatial domain 3

Lecture8.1

Lecture8.2

Lecture8.3


Image Segmentation 8

Lecture9.1

Lecture9.2

Lecture9.3

Lecture9.4

Lecture9.5

Lecture9.6

Lecture9.7

Lecture9.8


Image Processing New Video 2

Lecture10.1

Lecture10.2


Digital Signal Processing Notes 2

Lecture11.1

Lecture11.2


Image Processing Notes 2

Lecture12.1

Lecture12.2


DSIP Notes 1

Lecture13.1

Find Linear Convolution Part #1
Find Linear Convolution Part #1
In this video we have explain the basic concept to solve the sum of Linear convolution.
Linear convolution is the basic operation to calculate the output for any linear timeinvariant system given its input and its impulse response. The linear convolution result of two arbitrary M × N and P × Q image functions will generally be (M + P − 1) × (N + Q − 1), hence we would like the DFT G ˆ ˜ to have these dimensions. Therefore, the M × N function f and the P × Q function h must both be zeropadded to size (M + P − 1) × (N + Q − 1).
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