Python Digital Image Processing From Ground Up™
- 4.2
-
![]()
![]()
![]()
![]()
Brief Introduction
Image Processing : Edge-Detection Algorithms , Convolution, Filter Design, Gray-Level Transformation, Histograms etc.Description
With a programming based approach, this course is designed to give you a solid foundation in the most useful aspects of Image Processing in an engaging and easy to follow way. The goal of this course is to present practical techniques while avoiding obstacles of abstract mathematical theories. To achieve this goal, the image processing techniques are explained in plain language, not simply proven to be true through mathematical derivations.
Still keeping it simple, this course comes in different programming languages so that students can put the techniques to practice using a programming language of their choice. This version of the course uses the Python programming language.
By the end of the course you should be able to perform 2-D Discrete Convolution with images in python, perform Edge-Detection in python , perform Spatial Filtering in python, compute an Image Histogram and Equalize it in python, perform Gray Level Transformations, suppress noise in images, understand all about operators such as Laplacian, Sobel, Prewitt, Robinson, even give a lecture on image processing and more. Please take a look at the full course curriculum.
REMEMBER : I have no doubt you will love this course. Also it comes with a FULL money back guarantee for 30 days! So put simply, you really have nothing to loose and everything to gain.
Sign up and lets start manipulating some pixels.
Requirements
- Requirements
- No programming experience needed - I'll teach you everything you need to know
- No paid software required
- I'll walk you through, step-by-step on how to download and install Python
Knowledge
- Be able to suppress noise in images
- Be able to develop the 2-D Convolution algorithm in Python
- Apply Edge-Detection Operators like Laplacian, Sobel, Prewitt, Robinson etc. on Images
- Be able to develop Spatial Filtering Algorithms in Python
- Be able to compute an Image Histogram and Equalize it in Python
- Understand all about operators such as Laplacian, Sobel, Prewitt, Robinson etc.
- Be able to perform Image Processing using Python's Imaging Library
- Be able to perform Image Processing using SKImage
- Be able to perform Arithmetic and Boolean Operations like Addition, Subtraction, AND, OR etc. on images
- Be able to perform Image Enhancement Techniques such as Blurring and Sepia using Python
- Be able to give a lecture on Digital Image Processing
Israel Gbati
4.2 Raiting
Digital Signal Processing (DSP) From Ground Up™ in Python
- 4.3
-
![]()
![]()
![]()
![]()
![]()
Practical DSP in Python : Over 70 examples, FFT,Filter Design, IIR,FIR, Window Filters,Convolution,Linear Systems etc This version of the course uses the Python programming language....
{ C } Digital Image Processing From Ground Up™
- 3.8
-
![]()
![]()
![]()
![]()
![]()
Image Processing : Edge-Detection Algorithms , Convolution, Filter Design, Gray-Level Transformation, Histograms etc. The goal of this course is to present practical techniques while avoiding obstacles of abstract mathematical theories....
Python Digital Image Processing From Ground Up™
- 4.2
-
![]()
![]()
![]()
![]()
![]()
Image Processing : Edge-Detection Algorithms , Convolution, Filter Design, Gray-Level Transformation, Histograms etc. The goal of this course is to present practical techniques while avoiding obstacles of abstract mathematical theories....
