4.25 out of 5
4.25
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C ++Image Processing From Ground Up™

Build an Image Processing Library in C++
Instructor:
Israel Gbati
246 students enrolled
English [Auto-generated]
Build a Complete Image Processing Library in C++
Be able to develop the 2-D Convolution algorithm in C++
Be able to develop Spatial Filtering Algorithms in C++
Be able to compute an Image Histogram and Equalize it in C++
Be able to develop Gray Level Transformation Algorithms in C++
Be able to perform Geometric Operations on Images
Be able to perform Image Enhancement Techniques such as Blurring and Sepia
Be able to suppress noise in images
Be able to give a lecture on Digital Image Processing
Understand all about operators such as Laplacian, Sobel, Prewitt, Robinson etc.
Apply Edge-Detection Operators like Laplacian, Sobel, Prewitt, Robinson etc. on Images
Be able to perform Arithmetic and Boolean Operations like Addition, Subtraction, AND, OR etc. on images

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 C ++  programming language.

By the end of the course you should be able to develop the 2-D Discrete Convolution algorithm in C++, develop Edge-Detection Algorithms in C++, develop Spatial Filtering Algorithms in C++, compute an Image Histogram and Equalize it in C++, to develop Gray Level Transformation Algorithms, suppress noise in images, understand all about operators such as Laplacian, Sobel, Prewitt, Robinson, even give a lecture on image processing and so much 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.

Introduction

1
Introduction

Setting Up

1
Installing our Development Environment
2
Overview of CodeBlocks

Basic Image Processing Concepts and Terminologies

1
Overview of Image Processing
2
Understanding Image Color and Resolution
3
Understanding Image Formats and Data types
4
The Bitmap Format
5
Notice
6
Coding : Opening and Copying an Image
7
Coding : Creating an ImageReader and ImageWriter Function
8
Coding : Creating the Image Processing Library (Part I)
9
Coding : Creating the Image Processing Library (Part II)
10
Overview of Image Processing Techniques
11
Getting familiar with some commonly used terms
12
Overview of Image Processing Applications in Computer Vision

Arithmetic Operations

1
Effects of Addition and Subtraction on Images
2
Coding : Increasing Image Brigthness
3
Coding : Reducing Image Brightness

Histogram and Equalization

1
Introduction to Image Histogram
2
Understanding Histogram Equalization
3
GNU Plot Setup Notice
4
Downloading GNU Plot
5
Setting Up GNU Plot
6
Overview of GNU Plot
7
Plotting Multiple Signals
8
Coding : Computing the Histogram of an Image
9
Coding : Equalizing an Image Histogram
10
Introduction to Adaptive Thresholding

Geometric Operations

1
Introduction to Geometric Operations
2
Mapping and Affine Transformation
3
Exercise Notice
4
Coding : Rotating Images

Gray Level Transformation

1
Introduction to Gray Level Transformation
2
Coding : Experimenting with the Negative Transformation

Image Enhancement Techniques

1
Introduction to Image Enhancement
2
The Filter Kernel
3
Exercise Notice
4
Coding : Blurring an Image with a Filter Kernel
5
Exercise Notice
6
Coding : Creating a Sepia filter

Edge Detection

1
Coding : Detecting Lines with a Line Detector Mask
2
Understanding the Concept of Operators
3
Coding : Detecting Edges with the Prewitt Mask
4
Coding : Detecting Edges with the Sobel Mask
5
Coding : Detecting Edges with the Robinson Mask
6
Coding : Detecting Edges with the Kirsch Mask
7
Coding : Detecting Edges with the Laplacian Mask
8
Coding : Detecting Edges with the Robert's Mask

Neighborhood Processing

1
Introduction to Neighborhood Processing
2
Convolution And Correlation
3
Introduction to 2-D Convolution and Correlation
4
Introduction of Low-pass Filters
5
Coding : Developing the 2-D Discrete Convolution Algorithm

Filter Algorithms

1
Introduction of Low-pass Filters
2
Coding : Adding Salt and Pepper Noise to an Image
3
Coding : Performing High-pass Spatial Filtering
4
Coding : Generating Gaussian Noise from an Image
5
Coding : Developing the Maximum Filter Algorithm
6
Coding : Developing the Median Filter Algorithm
7
Coding : Developing the Minimum Filter Algorithm

Image Formation

1
Understanding how images are formed
2
Understanding the mathematics of image formation
3
Understanding the relevance of the point-spread-function (PSF)
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Includes

8 hours on-demand video
5 articles
Full lifetime access
Access on mobile and TV
Certificate of Completion