1 introduction image processing chapter1 digital image processing

7/23/2019 1 Introduction Image Processing Chapter1 Digital Image Processing

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© Oxford University Press 2011

Digital Image ProcessingDigital Image Processing

S. Sridhar S. Sridhar , Associate Professor,Department of Information Science and

Technoo!y, "oe!e of #n!ineerin!$%indy "amp%s, Anna University,

"hennai




Chapter 1Chapter 1

Introduction to Image ProcessingIntroduction to Image Processing




&at%re of Ima!e Processin!

' Ima!es are every(here) So%rces of Ima!es arepaintin!s, photo!raphs in ma!a*ines, +o%rnas, Ima!e!aeries, di!ita i-raries, ne(spapers, advertisement-oards, teevision and Internet.

' Ima!es are imitations of Ima!es.

' In ima!e processin!, the term /ima!e is %sed to denote

the ima!e data that is samped, %anti*ed, and readiyavaia-e in a form s%ita-e for f%rther processin! -ydi!ita comp%ters.




IMAGE PROCESSIG

#&I3O&4#&T




3efective mode Ima!in!

' Reflective mode imaging represents the

simpest form of ima!in! and %ses asensor to ac%ire the di!ita ima!e. A

video cameras, di!ita cameras, and

scanners %se some types of sensors for

capt%rin! the ima!e.




Emissive type imaging

' Emissive type imaging is the second type, (here

the ima!es are ac%ired from sef5%mino%s

o-6ects (itho%t the hep of a radiation so%rce. Inemissive type ima!in!, the o-6ects are sef5

%mino%s. The radiation emitted -y the o-6ect is

directy capt%red -y the sensor to form an

ima!e. Therma ima!in! is an exampe of

emissive type ima!in!.


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Transmissive imaging

' Transmissive imaging is the third type,

(here the radiation so%rce i%minates theo-6ect. The a-sorption of radiation -y the

o-6ects depends %pon the nat%re of the

materia. Some of the radiation passes

thro%!h the o-6ects. The atten%atedradiation is sensed into an ima!e.



Ima!e Processin!

' Optical image processing is an area that deas(ith the o-6ect, optics, and ho( processes areappied to an ima!e that is avaia-e in the form

of refected or transmitted

' Analog image processing is an area that deas(ith the processin! of anao! eectrica si!nas

%sin! anao! circ%its. The ima!in! systems that%se fim for recordin! ima!es are aso 7no(n asanao! ima!in! systems.



8hat is Di!ita Ima!e Processin!9

' Digital image processing is an area that

%ses di!ita circ%its, systems, and soft(are

a!orithms to carry o%t the ima!e

processin! operations. The ima!e

processin! operations may inc%de %aity

enhancement of an ima!e, co%ntin! ofo-6ects, and ima!e anaysis.



Reasons !or Popularit" o! DIP

1. It is easy to post5process the ima!e. Sma correctionscan -e made in the capt%red ima!e %sin! soft(are.

2. It is easy to store the ima!e in the di!ita memory.

:. It is possi-e to transmit the ima!e over net(or7s. Sosharin! an ima!e is %ite easy.

;. A di!ita ima!e does not re%ire any chemicaprocess. So it is very environment friendy, as harmf%fim chemicas are not re%ired or %sed.

<. It is easy to operate a di!ita camera.



IMAGE PROCESSIG AD

RE#A$ED %IE#DS



3eations (ith other -ranches

' Ima!e processin! deas (ith raster data or-itmaps, (hereas comp%ter !raphics primariy

deas (ith vector data.

' In di!ita si!na processin!, one often deas (iththe processin! of a one5dimensiona si!na. In

the domain of ima!e processin!, one deas (ithvis%a information that is often in t(o or moredimensions.




' The main !oa of machine vision is to

interpret the ima!e and to extract its

physica, !eometric, or topoo!ica

properties. Th%s, the o%tp%t of ima!e

processin! operations can -e s%-6ected to

more techni%es, to prod%ce additionainformation for interpretation.




' Ima!e processin! is a-o%t sti ima!es.

Th%s, video processin! is an extension of

ima!e processin!. In addition, ima!es are

stron!y reated to m%timedia, as the fied

of m%timedia -roady inc%des the st%dy of

a%dio, video, ima!es, !raphics, andanimation.




' Optica ima!e processin! deas (ith

enses, i!ht, i!htin! conditions, and

associated optica circ%its. The st%dy of

enses and i!htin! conditions has an

important roe in the st%dy of ima!e

processin!.




' Ima!e anaysis is an area that concernsthe extraction and anaysis of o-6ect

information from the ima!e. Ima!in!appications invove -oth simpe statisticss%ch as co%ntin! and mens%ration and

compex statistics s%ch as advancedstatistica inference. So statistics pay animportant roe in ima!in! appications.



Di!ita Ima!e

' An ima!e can -e defined as a 2D si!na

that varies over the spatia coordinates x

and y , and can -e (ritten mathematicay

as f = x , y >.



Di!ita Ima!e

' The va%e of the f%nction f = x , y > at every pointindexed -y a ro( and a co%mn is caed greyvalue or intensity of the ima!e.

' 3eso%tion is an important characteristic of anima!in! system. It is the a-iity of the ima!in!system to prod%ce the smaest discerna-edetais, i.e., the smaest si*ed o-6ect ceary, anddifferentiate it from the nei!h-o%rin! smao-6ects that are present in the ima!e.



Usef% definitions

' Ima!e reso%tion depends on t(o factors?optica reso%tion of the ens and spatiareso%tion. A %sef% (ay to define reso%tion isthe smaest n%m-er of ine pairs per %nitdistance.

' Spatia reso%tion depends on t(o parameters?the n%m-er of pixes of the ima!e and then%m-er of -its necessary for ade%ate intensityreso%tion, referred to as the -it depth.



Usef% definitions

' The n%m-er of -its necessary to encodethe pixe va%e is caed bit depth. @it depth

is a po(er of t(o it can -e (ritten aspo(ers of 2.

' So the tota n%m-er of -its necessary to

represent the ima!e is' &%m-er of ro(s B &%m-er of co%mns C

@it depth



$&PES O% IMAGES



$"pes o! Images 'ased on

Colour

$rey scae ima!es are different from-inary ima!es as they have many shades

of !rey -et(een -ac7 and (hite. Theseima!es are aso caed monochromatic asthere is no coo%r component in the

ima!e, i7e in -inary ima!es. Grey scale isthe term that refers to the ran!e of shades-et(een (hite and -ac7 or vice versa.



Types of Ima!es

' In -inary ima!es, the pixes ass%me a va%e of 0or 1. So one -it is s%fficient to represent the pixeva%e. @inary ima!es are aso caed -i5eve

ima!es.

' In tr%e coo%r ima!es, the pixe has a coo%r thatis o-tained -y mixin! the primary coo%rs red,

!reen, and -%e. #ach coo%r component isrepresented i7e a !rey scae ima!e %sin! ei!ht-its. 4osty, tr%e coo%r ima!es %se 2; -its torepresent a the coo%rs.



Indexed Ima!e

' A specia cate!ory of coo%r ima!es is the

indexed ima!e. In most ima!es, the f%

ran!e of coo%rs is not %sed. So it is -etter

to red%ce the n%m-er of -its -ymaintainin! a coo%r map, !am%t, or

paette (ith the ima!e.




Pse%docoo%r Ima!e

' i7e tr%e coo%r ima!es, Pse%docoo%rima!es are aso %sed (idey in ima!e

processin!. Tr%e coo%r ima!es are caedthree5-and ima!es. o(ever, in remotesensin! appications, m%ti5-and ima!es

or m%ti5spectra ima!es are !eneray%sed. These ima!es, (hich are capt%red-y sateites, contain many -ands.




Types of Ima!es -ased on

Dimensions

' $"pes o! Images 'ased on Dimensions

2D and :D' $"pes o! Images 'ased on Data $"pes

' Sin!e, do%-e, Si!ned or %nsi!ned.




DIGI$A# IMAGE PROCESSIG

OPERA$IOS




Ima!e Anaysis




Ima!e #nhancement




Ima!e 3estoration




Ima!e "ompression




Ima!e Anaysis




Ima!e Synthesis




Ima!e Processin! Appications




Di!ita Ima!in! System




"omponents

1 introduction image processing chapter1 digital image processing

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