Image Processing Basics

1. Digital Image processing
What is an image?
An image is defined as a two-dimensional function, F(x,y), where x and y are
spatial coordinates, and the amplitude of F at any pair of coordinates (x,y) is
called the intensity of that image at that point. When x,y, and amplitude values
of F are finite, we call it a digital image.
In other words, an image can be defined by a two-dimensional array specifically arranged in rows and columns.
Digital Image is composed of a finite number of elements, each of which elements have a particular value at a
particular location.These elements are referred to as picture elements ,image elements,and pixels.
A Pixel is most widely used to denote the elements of a Digital Image

2. Image as a Matrix
As we know, images are represented in rows and columns we have the
following syntax in which images are represented:
The right side of this equation is digital image by definition. Every element of this matrix
is called image element , picture element , or pixel.

3. Introduction to the Image processing
□ Image processing is a method to perform some operations on an image, in
order to get an enhanced image or to extract some useful information from
it. It is a type of signal processing in which input is an image and output
may be image or characteristics/features associated with that image.
□ Image processing basically includes the following three steps:
▪ Importing the image via image acquisition tools
▪ Analyzing and manipulating the image;
▪ Output in which result can be altered image or report that is based on
image analysis.

4. Introduction to the Image processing
There are two types of methods used for image
processing namely, analogue and digital image processing.
□ Analogue image processing can be used for the hard copies like printouts
and photographs. Image analysts use various fundamentals of
interpretation while using these visual techniques.
□ The analog image processing is applied on analog signals and it processes
only two-dimensional signals. The images are manipulated by electrical
signals. In analog image processing, analog signals can be periodic or
non-periodic
Examples of analog images are television images, photographs, paintings,

5. Introduction to the Image processing
□ Digital image processing techniques help in manipulation of the digital
images by using computers.
□ A digital image processing is applied to digital images (a matrix of small
pixels and elements). For manipulating the images, there is a number of
software and algorithms that are applied to perform changes. Digital image
processing is one of the fastest growing industry which affects everyone's
life.
Examples of digital images are color processing, image recognition, video
processing, etc

6. Introduction to the Image processing

7. Analog Image Processing vs. Digital Image Processing
quality of images.
Analog Image Processing Digital Image Processing
The analog image processing is applied on The digital image processing is applied to digital
analog signals and it processes only signals that work on analyzing and manipulating the two-
dimensional signals. images.
Analog signal is time-varying signals so the It improves the digital quality of the image and
images formed under analog image intensity distribution is perfect in it.
processing get varied.
Analog image processing is a slower and Digital image processing is a cheaper and fast image
costlier process. storage and retrieval process.
Analog signal is a real-world but not good It uses good image compression techniques that
reduce the amount of data required and produce good
quality of images
into tiny components.
It is generally continuous and not broken It uses an image segmentation technique which is used
to detect discontinuity which occurs due to a broken
connection path.

8. Introduction to the DIP
□ 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.
□ Digital Image Processing is a software which is used in image processing.
For example: computer graphics, signals, photography, camera
mechanism, pixels, etc.
□ Digital Image Processing provides a platform to perform various
operations like image enhancing, processing of analog and digital signals,
image signals, voice signals etc.

9. Introduction to the DIP

10. Introduction to the DIP

11. Different Dimention
1-D Pictures: One-dimensional pictures are those containing only one dimension.
This is only possible when you're dealing with a line, as the only dimension you
have is length.
2-D Pictures: One type of picture you can come across in real life is the two-
dimensional one. The two dimensions depicted are length and width and the
objects on the picture are flat.
3-D Pictures: Three-dimensional pictures contain yet another dimension: depth.
This type is the most realistic one, as the depiction of objects or environments
resembles the way we see them through our own eyes

12. Different Dimention

13. Concept of Pixel
The full form of the pixel is "Picture Element." It is also known as "PEL." Pixel
is the smallest element of an image on a computer display, whether they are
LCD or CRT monitors. A screen is made up of a matrix of thousands or
millions of pixels. A pixel is represented with a dot or a square on a computer
screen.

14. Concept of Pixel
Each pixel has a value, or we can say a unique logical address. It can have only one color at
a time. Colour of a pixel is determined by the number of bits which is used to represent it. A
resolution of a computer screen depends upon graphics card and display monitor, the
quantity, size and color combination of pixels.

15. Concept of Pixel

16. Concept of Pixel

17. Calculation of the total number of pixels
Below is the formula to calculate the total number of pixel in an
image.
For example: let rows=300 & columns=200
Total number of pixels= 300 X 200
= 500

18. Concept of Pixel
Pixel value(0)
As we know that each pixel has a unique value. 0 is a unique value that means the absence
of light. It means that 0 is used to denote dark.
We have a matrix of 3X3 of an image, and each pixel is of value as shown below:
It means the image formed is of 9 pixels which are black.
The image would be something as below:

19. Types of an image
BINARY IMAGE– The binary image as its name suggests, contain only two pixel
elements i.e 0 & 1,where 0 refers to black and 1 refers to white. This image is also known
as Monochrome.
It is the simplest type of image. It takes only two values i.e, Black and White or 0 and 1.
The binary image consists of a 1-bit image and it takes only 1 binary digit to represent a
pixel. Binary images are mostly used for general shape or outline.

20. Types of an image
Gray-scale images
Grayscale images are monochrome images, Means they have only one color. Grayscale
images do not contain any information about color. Each pixel determines available
different grey levels.
A normal grayscale image contains 8 bits/pixel data, which has 256 different grey levels.

21. Types of an image
Colour images
Colour images are three band monochrome images in which, each band contains a different
color and the actual information is stored in the digital image. The color images contain
gray level information in each spectral band.
The images are represented as red, green and blue (RGB images). And each color image
has 24 bits/pixel means 8 bits for each of the three color band(RGB).

22. Types of an image

23. Pixels, Dots, and Lines per Inch
Megapixels
A digital camera uses pixel elements (also known as a pixel) to
capture images. More number of pixels makes the better
resolution of that image.
Formula to calculate megapixel of a camera:

24. Pixels, Dots, and Lines per Inch
Example:
Let's take dimension of an image: 2500 X 3192
So, according to formula
(2500 * 3192) / 1 Million = 7.9 = 8 megapixel
(approx).

25. Pixels, Dots, and Lines per Inch
Aspect ratio:
Aspect ratio is the ratio between height and width of an image. A colon is used to
separate two numbers. Different images on different screens have a different
ratio.
Essentially, it describes an image's shape. Aspect ratios are written as a formula
of width to height, like this: 3:2. For example, a square image has an aspect ratio
of 1:1, since the height and width are the same.
Common aspect ratio is as follows:
1.33:1, 1.37:1, 1.43:1, 1.50:1, 1.56:1, 1.66:1, 1.75:1, 1.78:1, 1.85:1, 2.00:1, e.t.c
Advantage
1. It maintains balance in the appearance of an image (ratio between horizontal and vertical
pixel).
2. When the aspect ratio is increased, images do not distort.

26. Pixels, Dots, and Lines per Inch
Math-01: Here is a grayscale image given with aspect ratio 2:5, and the resolution of the image is 480000
pixels.
Calculate the following things:
□ Dimensions of the image.
□ R =?
□ C =?
□ Size of the image.

27. Pixels, Dots, and Lines per Inch
Comparing equation 1 and equation 2