Digital image processing deals with manipulation of digital images through a digital computer. It is a subfield of signals and systems but focus particularly on images. DIP focuses on developing a computer system that is able to perform processing on an image. The input of that system is a digital image and the system process that image using efficient algorithms, and gives an image as an output. The most common example is Adobe Photoshop. It is one of the widely used application for processing digital images.

How it works.

In the above figure, an image has been captured by a camera and has been sent to a digital system to remove all the other details, and just focus on the water drop by zooming it in such a way that the quality of the image remains the same.

This tutorial gives you the knowledge of widely used methods and procedures for interpreting digital images for image enhancement and restoration and performing operations on images such as (blurring , zooming , sharpening , edge detection , e.t.c). It also focuses on the understanding of how the human vision works. How do human eye visualize so many things , and how do brain interpret those images? The tutorial also covers some of the important concepts of signals and systems such as (Sampling , Quantization , Convolution , Frequency domain analysis e.t.c).

Signals and systems

Since DIP is a subfield of signals and systems , so it would be good if you already have some knowledge about signals and systems , but it is not necessary. But you must have some basic concepts of digital electronics.

Calculus and probability

Basic understanding of calculus , probability and differential equations is also required for better understanding.

Basic programming skills

Other than this, it requires some of the basic programming skills on any of the popular languages such as C++ , Java , or MATLAB.

Course Content

Digital Image Processing
DIP Home
DIP Image Processing Introduction
DIP Signal and System Introduction
DIP History of Photography
DIP Applications and Usage
DIP Concept of Dimensions
DIP Image Formation on Camera
Types of Images
DIP Camera Mechanism
DIP Concept of Pixel
DIP Perspective Transformation
DIP Concept of Bits Per Pixel
DIP Types of Images
DIP Color Codes Conversion
DIP Grayscale to RGB Conversion
DIP Concept of Sampling
DIP Pixel Resolution
DIP Concept of Zooming
DIP Zooming methods
DIP Spatial Resolution
DIP Pixels Dots and Lines per inch
DIP Gray Level Resolution
DIP Concept of Quantization
DIP ISO Preference curves
DIP Concept of Dithering
DIP Histograms Introduction
DIP Brightness and Contrast
DIP Image Transformations
DIP Histogram Sliding
DIP Histogram Stretching
DIP Introduction to Probability
DIP Histogram Equalization
DIP Gray Level Transformations
DIP Concept of convolution
DIP Concept of Masks
DIP Concept of Blurring
DIP Concept of Edge Detection
Prewitt Operator
Sobel Operator
DIP Robinson Compass Mask
DIP Krisch Compass Mask
Laplacian Operator
DIP Frequency Domain Analysis
DIP Fourier series and Transform
DIP Convolution theorm
DIP High Pass vs Low Pass Filters
DIP Introduction to Color Spaces
DIP JPEG compression
DIP Optical Character Recognition
DIP Computer Vision and Graphics
DIP Quick Guide
DIP Useful Resources
Discuss DIP

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