digital image processing seminar ppt

7/21/2019 Digital Image Processing Seminar PPT

http://slidepdf.com/reader/full/digital-image-processing-seminar-ppt 1/23

Under Guidance of:

Dr. U. P. Singh

PresentedBy:

Suryanshu

Satapathy



ONTENTS

#his presentation co$ers:

What is a image?

What is digital image?

What is digital image processing?

Key Stages In Digital Image Processing

Applications



WHAT IS AN IMAGE?

An image, derived from a Latin word imago, stands for an

artifact, such as a two dimensional picture, that has a similarappearance to some su!ect"usually a physical o!ect or a person#

SIMPLE MODEL:

Image refers to a two dimensional light intensity function denotedy f$%,y& ' % and y denote the spatial co'ordinates# (he magnitudeof f$ & at spatial co'ordinates $%,y& gives the intensity of image atthat point#

f$%,y& can e characteri)ed y two components' (he amount of source light eing incident on the scene eing

viewed * illumination component $i$%,y&&#

(he amount of light reflected y the o!ects in the scene *reflectance com onent r %, #



+ow, f$%,y& i$%,y&-r$%,y& 0 < i(x,y) < ∞ 0 < r(x,y) < 1

f$%,y& can e treated as an .%+ array for processing, where .and + are the dimension of the image along / and 0 directions#

1ach element of the array represents the intensity values and can

e called as pi%el or pel#

1 pixel



%S&'U#(&) &* +) (+G:

the dpi $dots per inch pi%els per inch& of an image#

(he resolution of a digital image is defined as the numer of pi%els it

contains# (he higher the resolution, the higher the print 2uality and the

larger the data si)e of the image $in 3iloytes or megaytes&

#-PS &* (+G:

Color Image(R,Y,B-each 0~255)

Intensity (Gray level image)(0~255)

Binary Image(0~1)



(+G: +P'S

Colore!Image

Gray level Image

Binary Image



WHAT IS A DI GITAL IMAGE?

Processing of a picture or image y digital computer, 4ut computer

processes only digital data# So we need a digital image#

Continuos

Image

Digital

imageSampling and

quantization

Obtaining a digital Image :

Digiti)ation of the spatial co'ordinates $%,y& is called image

sampling#

(he amplitude digiti)ation is called gray'level 2uanti)ation



We usually operate on digital $discrete& images y5

Sample the 6D space on a regular grid

7uanti)e each sample $round to nearest integer&

If our samples are D apart, we can write this as5

f 8i , j 9 7uanti)e: f $i D, j D& ;

(he image can now e represented as a matri% of integervalues



%esu/t &f

S+P'()G

+)D

U+)#(+#(&)



WHAT IS DI GITAL IMAGE

PRO ESSING?

Processing descries the act of ta3ing something through an estalished

and usually routine set of procedures to convert it from one form toanother, such as processing mil3 into cheese#

Image processing is a form of signal processing for which the input is

an image, such as photographs or frames of video< the output of image

processing can e either an image or a set of characteristics or

parameters related to the image# .ost image processing techni2uesinvolve treating the image as a two'dimensional signal and applying

standard signal'processing techni2ues to it#

(he following e%ample represents a asic operation of image processing

#he coposite iage "4

has 5een sp/it into red 14,

green 24 and

5/ue 34 channe/s



(+GP%&6SS()G An image processing operation typically defines a new image g in

terms of an e%isting image f

We can transform either the range of =t>5

r the domain of = f’ 5



Why ?

@odingcompression 1nhancement, restoration, reconstruction

Analysis, detection, recognition, understanding

Bisuali)ation

(o improve image 2uality for human perception andorcomputer interpretation

Processing of image data for storage and transmission#

Image Image

processing

Better

image

Image Image

processingCompressed

Image



+ #-P(6+' D(G(#+' (+G P%&6SS()GSU)6

Record

outputDisplay

object observe

Imagingsystems

digitize

Sampleand

quantize

store

Digital

storage

dis!"

process

Digitalcomputer

Re#res$%

store

&n'linebu##er

Image (cquisition )rocessing Display%Storage

% *ransmission



KEY STAGES IN DIGITAL IMAGE

PRO ESSING

Image

(cquisition

Image

Restoration

Segmentation

Representation

+ Description

Image,n$ancement

&bject

Recognition

)roblem Domain

Colour Image

)rocessingImage

Compression



I.AC1 A@7ISI(I+

Images are generated y the comination of an illumination source

and the reflection or asorption of energy from that source y the

elements of the scene eing imaged# Eor eg# Bisile light source

illuminates a common everyday F'D scene#

(o get a 6'D picture of the scene we can use a camera which contains

light sensors#

(he reflected light from the scene eing imaged is focused y thecamera lens

Light falls on the sensing material $a @@D array& and produces

electrical signals proportional to the light intensity

An AD converter converts this signal to a set of discrete numers#

$Cray level 2uanti)ation&#

The illumination may originate from a source of electromagnetic energy

such as radar, infrared, X-ray…

Scene elements can e familiar o!ects or may e a molecule, uried roc"

formations, human rain…



IMAGE ENHANCEMENT

(o process an image so that the result is more suitale than the

original image for a specific application Accentuate certain image features for suse2uent analysis or for image

display

@ontrast enhancement, noise filtering, sharpening, magnifyingG

HICI+AL I.AC1 IC PASS EIL(1H1D I.AC1



IMAGE RESTORATION

A class of methods that aim to remove or reduce the degradations

that were incurred while the digital image eing otained# (he degradations can occur due to5'

Sensor noise

#lur due to camera misfocus

$elati%e o!ect camera motion

$andom atmos&heric turulence

&riginal image Distorted imageRandom -oise"



IMAGE COMPRESSION

(he storage re2uirement for images are high#

Heduce the numer of its re2uires to represent an image#

4y compressing an image we can reduce the memory needed to store

the image, reduce the time re2uired for transmission, also reduction in

andwidth

SEGMENTATIONPartition of an image into its constituent parts or o!ects#

Involves feature selectionIdentification and feature e%traction#



APPLI ATIONS(NAMING A

FEW…)

uman operators are

e%pensive, slow and unreliale

ma3e machines do the !o

instead industrial vision

systems are used in all 3inds of

industries

1.

()DUS#%(+' ()SP6#(&)



(a3e slice from .HI scan of canine heart, and find

oundaries etween types of tissue

Image with grey levels representing tissue density

se a suitale filter to highlight edges

Original MRI Image of a DogHeart

Edge Detection Image

D(6()



B(&#%(6S+S#%&)&-



#%+**(6 &)(#&%D&6U)# +)D'()G



T H A N

Y O U

digital image processing seminar ppt

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