Dip review

DIGITAL IMAGE PROCESSING

Presented by:- S. Sushma(11MD1A0466) P. Harish Reddy(11MD1A0496) V. Manikanta(11MD1A04B1)

One picture is more than ten thousand words

INTRODUCTIONWhat is an Image

An image is nothing more than a two dimensional signal. It is defined by the mathematical function f(x,y) where x and y are the two co-ordinates horizontally and vertically.The value of f(x,y) at any point is gives the pixel value at that point of an image.

X

YThe adjacent figure is an example of digital image that we can watch on our computer screen. But actually , this image is nothing but a two dimensional array of numbers ranging between 0 and 255.

Adjacent table is the actual representation of above image.Each number represents the value of the function f(x,y) at any point. In this case the value 123 , 232,123 each represents an individual pixel value.

INTRODUCTION 123

30

123

232

123

321

123

77

89

80

255

255

PIXEL

A Pixel is a basic building block for an image.

1 pixel

What is a Digital Image?A digital image is a representation of a two-dimensional image as a finite set of digital values, called picture elements or pixels

How a Digital Image is Generated

Since capturing an image from a camera is a physical procedure. The sunlight is used as a source of energy. A sensor array is used for the acquisition of the image. So when the sunlight falls upon the object, then the amount of light reflected by that object is sensed by the sensors, and a continuous voltage signal is generated by the amount of sensed data.

In order to create a digital image , we need to convert this data into a digital form.

This involves sampling and quantization.

The result of sampling and quantization results in an two dimensional array or matrix of numbers which are nothing but a digital image.

How a Digital Image is Generated

Meaning of digital image processing

Digital : Information represented in discrete (digits) form. Image : A reproduction of the form of a person or object . Processing : Performing a series of actions or operations on data to

convert into information DIP: The Digital image processing is the use of computer

algorithms to perform image processing (or) manipulation on digital images.

HISTORY OF DIP

Early 1920s: One of the first applications of digital imaging was in the news paper industry.

The Bartlane cable picture transmission service.

Images were transferred by

submarine cable between London and New York.

Pictures were coded for cable transfer and reconstructed at the receiving end on a telegraph printer.

Fig. 2 Fig. 3

In 1921, photographic printing press improved the resolution and tonal quality of images.

Bartlane system was capable of coding 5 distinct brightness levels.

It increased to 15 by 1929.

HISTORY OF DIP

After 35 years of improvement in processing technique

In 1964, Computer processing techniques were used to improve picture of moon transmitted by Ranger 7 at JPL.

This was the basis of modern image processing technique.

HISTORY OF DIP

Many of the techniques of digital image processing, were developed in the 1960s at the Jet Propulsion Laboratory, Massachusetts Institute of Technology, Bell Laboratories, University of Maryland, and a few other research facilities, with application to satellite imagery, wire-photo standards conversion, Medical imaging, Videophone, Character recognition, and photograph enhancement. In 2002 Raanan Fattal introduced Gradient domain image processing, a new way to process images in which the differences between pixels are manipulated rather than the pixel values themselves.

HISTORY OF DIP

http://en.wikipedia.org/wiki/Jet_Propulsion_Laboratory

http://en.wikipedia.org/wiki/Jet_Propulsion_Laboratory

http://en.wikipedia.org/wiki/MIT

http://en.wikipedia.org/wiki/Bell_Laboratories

http://en.wikipedia.org/wiki/University_of_Maryland,_College_Park

http://en.wikipedia.org/wiki/Satellite_imagery

http://en.wikipedia.org/wiki/Wirephoto

http://en.wikipedia.org/wiki/Medical_physics

http://en.wikipedia.org/wiki/Videophone

http://en.wikipedia.org/wiki/Character_recognition

http://en.wikipedia.org/wiki/Gradient_Domain_Image_Processing

HISTORY OF DIP

•1970s: Digital image processing begins to be used in medical applications•1979: Sir Godfrey N. Hounsfield & Prof. Allan

M. Cormack share the Nobel Prize in medicine

for the invention of tomography, the technology

behind Computerised Axial

Tomography (CAT) scans

Typical head slice CAT image

Godfrey N. Hounsfield Prof. Allan M. Cormack

Image processing is used for two somewhat different purposes:

Improving the visual appearance of images (pictorial information) to a human viewer, and

Preparing (processing) images for measurement of the features and structures present.

For efficient storage and transmission of images.

The techniques that are appropriate for each of these tasks are not always the same, but there is considerable overlap.


Low Level Process

Input: ImageOutput: Image

Examples: Noise removal, image sharpening

Mid Level Process

Input: Image Output: Attributes

Examples: Object recognition, segmentation

High Level Process

Input: Attributes Output: Understanding

Examples: Scene understanding, autonomous navigation

“The continuum from image processing to computer vision can be broken up into low , mid and high-level processes”


Low-level process: (DIP)Primitive operations where inputs and outputs are images Major functions: image pre-processing like noise reduction,

contrast enhancement, image sharpening, etc.

Mid-level process (DIP and Computer Vision and Pattern Recognition) Inputs are images, outputs are attributes (e.g., edges). Major functions: segmentation, description, classification /

recognition of objects

High-level process (Computer Vision)Make sense of an ensemble of recognized objects; perform the

cognitive functions normally associated with vision

Key Stages in Digital Image Processing

Image Acquisition

Image Restoration

Morphological Processing

Segmentation

Representation &

Description

Image Enhancemen

t

Object Recognition

Problem Domain

Colour Image

Processing

Image Compression

Fundamental steps in DIP

Image Acquisition:

First processInvolves image preprocessing viz. scaling

Image Enhancement:

Process of image manipulation to make it more suitable for specific useDifferent images require different enhancement methodsSubjective technique

Image Restoration:

Based on mathematical or probabilistic models of image degradation thus objective.

Fundamental steps in DIPColor Image Processing:Gained importance due to increase use of internet

Wavelets:Used mainly for image data compression & pyramidal representation where images are divided into smaller regions.

Compression:Technique for reducing the storage required to save image, or bandwidth required to transmit it. JPEG (Joint Photographic Experts Group) TIF(Tagged Image File) or TIFF(Tagged Image File Format) PNG(Portable Network Graphics) GIF(Graphics Interchange Format) BMP(Bitmap image file)

Fundamental steps in DIPMorphological Processing :

Deals with tools for extracting image components

Segmentation:

Partition an image into constituent parts or objects.

Representation & description:

Follows output of segmentation with raw pixel data usually boundary information or regional description.

Object recognition:

Process of assigning a label to an object based on its description.

Key Stages in Digital Image Processing:Image Aquisition

Image Acquisition

Image Restoration


Segmentation

Representation &

Description

Image Enhancemen

t

Object Recognition

Problem Domain

Colour Image

Processing

Image Compression

Key Stages in Digital Image Processing:Image Enhancement

Image Acquisition

Image Restoration


Segmentation

Representation &

Description

Image Enhancemen

t

Object Recognition

Problem Domain

Colour Image

Processing

Image Compression

Key Stages in Digital Image Processing:Image Restoration

Image Acquisition

Image Restoration


Segmentation

Representation &

Description

Image Enhancemen

t

Object Recognition

Problem Domain

Colour Image

Processing

Image Compression

Key Stages in Digital Image Processing:


Image Acquisition

Image Restoration


Segmentation

Representation &

Description

Image Enhancemen

t

Object Recognition

Problem Domain

Colour Image

Processing

Image Compression

Key Stages in Digital Image Processing:Segmentation

Image Acquisition

Image Restoration


Segmentation

Representation &

Description

Image Enhancemen

t

Object Recognition

Problem Domain

Colour Image

Processing

Image Compression

Key Stages in Digital Image Processing:Object Recognition

Image Acquisition

Image Restoration


Segmentation

Representation &

Description

Image Enhancemen

t

Object Recognition

Problem Domain

Colour Image

Processing

Image Compression

Key Stages in Digital Image Processing:Representation & Description

Image Acquisition

Image Restoration


Segmentation

Representation &

Description

Image Enhancemen

t

Object Recognition

Problem Domain

Colour Image

Processing

Image Compression

Key Stages in Digital Image Processing:Image Compression

Image Acquisition

Image Restoration


Segmentation

Representation &

Description

Image Enhancemen

t

Object Recognition

Problem Domain

Colour Image

Processing

Image Compression

Key Stages in Digital Image Processing:Colour Image Processing

Image Acquisition

Image Restoration


Segmentation

Representation &

Description

Image Enhancemen

t

Object Recognition

Problem Domain

Colour Image

Processing

Image Compression

Components of an Image Processing System

Network

Image Displays Computer Mass Storage

Hardcopy Image Processing Image Processing H/W S/W

Image Sensors Problem Domain


Sensors:Two elements required to acquire digital images Physical device: sensitive to the energy radiated by the object we wish to image.Digitizer: converts output of physical sensing device into digital form.Specialized image processing hardware: Digitizer + hardware Hardware: Performs Arithmetic Logic Unit (ALU) on entire image.Computer: Image processing system ranging from PC to supercomputerImage Processing Software: Specialized modules performing specific tasks


Mass Storage: Image of size 1024 * 1024 pixels with pixel intensity of 8-bit requires 1 Mb storage space.

Image Displays: Flat screen, TV, Monitors, LCD, LED, 3D displays

Hardcopy:Laser Printers, Camera Films, Heat Sensitive devices, inkjet units, digital units like optical and CD-ROM.

Networking:Communicating with remote sites on internet.

Applications of Digital Image Processing

1)Biological Research: DNA typing and matching;

Automatic counting and classification of cell structures in bone and tissue.

2) Defence and Intelligence:

Reconnaissance photo-interpretation of objects in

Satellite images;

Target acquisition and

Missile guidance.

3) Document Processing:

Scanning,

Archiving and transmission (fax);

Automatic detection and recognition of printed text (postal sorting office, tax return processing, banking cheques).

4) Law Enforcement Forensics:

Photo-ID kits,

criminal photo-search,

automatic fingerprint matching,

DNA matching and fibre analysis


5) Photography: Altering colours, Zooming;Adding and subtracting objects to a scene;

6) Remote Sensing:Land cover analysis (water, roads, cities and cultivation),

vegetation features (water content and temperature) and crop yield analysis;

3-D terrain rendering from satellite or aircraft data (road and dam planning); fire and smoke detection.


7) Space exploration and Astronomy:

Satellite navigation and altitude control using star positions.

8) Video and Film Special Effects: Animation, and

Special effects (Star Wars).


The imaging machines can cover almost the entire EM spectrum, ranging from gamma to radio waves. These include

• Gamma ray images• x-ray band images• ultra-violet band images• visual light and infra-red images• Imaging based on micro-waves and radio waves•Thus, digital image processing encompasses a wide and varied field of applications.

EM SPECTRUM:

Electro-Magnetic Spectrum

IR Imaging (Performance)

Fig. Thermal / IR view of a Chip

IR Imaging (Natural Calamity)

Fig. IR satellite view of Augustine volcano

IR Imaging (Night Vision)

Fig. IR image of a sloth at night

IR Imaging (Night Vision)

Fig. Night vision system used by soldiers

Ultrasound imaging (Medical)

Fig. Fetus and Thyroid using ultrasound

Seismic imaging (Earthquake)

Fig. Detecting Earthquakes and its cause using cross sectional view

UV imaging (Ozone)

Fig. Detect ozone layer damage

X-Ray imaging (Medical)

Fig. X ray of neck

X-Ray imaging (Medical)

Fig. X ray of head

Gamma-Ray imaging (Astronomy)

Fig. Gamma ray bursts in space

Gamma-Ray imaging (Medical)

Fig. Gamma ray exposed images

Remote Sensing

Fig. Satellite images of Mumbai suburban(Left) and Gateway of India (Right)

Remote Sensing

Advantages

Digital image processing made digital image can be noise free

It can be made available in any desired format. (X-rays, photo negatives, improved image, etc)

Digital imaging is the ability of the operator to post-process the image .It means manipulate the pixel shades to correct image density and contrast .

Images can be stored in the computer memory and easily retrieved on the same computer screen .

Digital imaging allows the electronic transmission of images to third-party providers

CONCLUSION

1.Dip is used to give effective images.2.It is used to edit image and manipulate as user desired.3.It is used in satellites ,medical, movies fields e.t.c.4.Colour images styles, animation so on…5.User understand any thing easy way.

Dip review

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