unit3 multimedia notes

8/18/2019 unit3 multimedia notes

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unit-3What is Image Processing?Image processing is a method to convert an image into digital form and performsome operations on it, in order to get an enhanced image or to extract some usefulinformation from it. It is a type of signal dispensation in which input is image, like

video frame or photograph and output may be image or characteristics associatedwith that image. Usually Image Processing system includes treating images as twodimensional signals while applying already set signal processing methods to them.

It is among rapidly growing technologies today, with its applications in various

aspects of a business. Image Processing forms core research area within

engineering and computer science disciplines too.

Image processing basically includes the following three steps.

· Importing the image with optical scanner or by digital photography.

·

Analying and manipulating the image which includes data compression and image

enhancement and spotting patterns that are not to human eyes like satellite

photographs.

· !utput is the last stage in which result can be altered image or report that is based

on image analysis.

Purpose of Image processing

"he purpose of image processing is divided into # groups. "hey are$

%. &isualiation ' !bserve the ob(ects that are not visible.

).

Image sharpening and restoration ' "o create a better image.

*. Image retrieval ' +eek for the image of interest.

. -easurement of pattern -easures various ob(ects in an image.

#. Image /ecognition 0istinguish the ob(ects in an image.

Types

"he two types of methods used for Image Processing are Analog and

Digital Image Processing. Analog or visual techni1ues of image processing can be

used for the hard copies like printouts and photographs. Image analysts use variousfundamentals of interpretation while using these visual techni1ues. "he image

processing is not (ust confined to area that has to be studied but on knowledge of

analyst. Association is another important tool in image processing through visual

techni1ues. +o analysts apply a combination of personal knowledge and collateral

data to image processing.

0igital Processing techni1ues help in manipulation of the digital images by using

computers. As raw data from imaging sensors from satellite platform containsdeficiencies. "o get over such flaws and to get originality of information, it has to


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undergo various phases of processing. "he three general phases that all types of

data have to undergo while using digital techni1ue are Pre' processing,

enhancement and display, information extraction.

1.1.3 Components of Image Processing System

i) Image Sensors

With reference to sensing, two elements are required to acquire digital image.

The rst is a physical device that is sensitive to the energy radiated by the object

we

wish to image and second is specialized image processing hardware.


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ii) Specialize image processing hardware –

t consists of the digitizer just mentioned, plus hardware that performs other

primitive

operations such as an arithmetic logic unit, which performs arithmetic such

addition

and subtraction and logical operations in parallel on images

iii) Computer

t is a general purpose computer and can range from a !" to a supercomputer

depending on the application. n dedicated applications, sometimes specially

designed

computer are used to achieve a required level of performance

iv) #oftware

t consist of specialized modules that perform specic tas$s a well designed

pac$age

also includes capability for the user to write code, as a minimum, utilizes the

specialized module. %ore sophisticated software pac$ages allow the integration

of

these modules.

v) ass storage –

This capability is a must in image processing applications. &n image of size '(*

+'(* pi+els ,in which the intensity of each pi+el is an - bit quantity requires

one

megabytes of storage space if the image is not compressed .mage processing

applications falls into three principal categories of storage

i) #hort term storage for use during processing

ii) n line storage for relatively fast retrieval

iii) &rchival storage such as magnetic tapes and dis$s

vi) mage displaysmage

displays in use today are mainly color T/ monitors. These monitors are driven


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by the outputs of image and graphics displays cards that are an integral part of

computer system

vii)0ardcopy devices -

The devices for recording image includes laser printers, lm cameras, heat

sensitive

devices in$jet units and digital units such as optical and "1 2% dis$. 3ilms

provide

the highest possible resolution, but paper is the obvious medium of choice for

written

applications.

viii) !etwor"ing

t is almost a default function in any computer system in use today because of

the large

amount of data inherent in image processing applications. The $ey consideration

in

image transmission bandwidth.

#undamental Steps in $igital Image Processing

There are two categories of the steps involved in the image processing 4

5') %ethods whose outputs are input are images.

5) %ethods whose outputs are attributes e+tracted from those images.

i) Image ac%uisition

t could be as simple as being given an image that is already in digital form.

6enerally

the image acquisition stage involves processing such scaling.

ii) Image &nhancement

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t is among the simplest and most appealing areas of digital image processing.

The idea

behind this is to bring out details that are obscured or simply to highlight certain

features of interest in image. mage enhancement is a very subjective area of

image


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processing.

iii) Image 'estoration –

t deals with improving the appearance of an image. t is an objective approach,

in the

sense that restoration techniques tend to be based on mathematical or

probabilistic

models of image processing. 9nhancement, on the other hand is based on

human

subjective preferences regarding what constitutes a :good; enhancement result

iv) "olor image processing 4

t is an area that is been gaining importance because of the use of digital imagesover

the internet. "olor image processing deals with basically color models and their

implementation in image processing applications.

v) (avelets and ultiresolution Processing

These are the foundation for representing image in various degrees of resolution

vi) Compression

t deals with techniques reducing the storage required to save an image, or the

bandwidth required to transmit it over the networ$. t has to major approaches

a)


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%9?2@6 #!&T&< 29#


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quantization

Dou can see in this image , that the signal has been quantied into three di>erent

levels. That means that when we sample an image , we actually gather a lot of

values, and in quantization , we set levels to these values. This can be more

clear in the image below.

quantization levels

n the gure shown in sampling , although the samples has been ta$en , but they

were still spanning vertically to a continuous range of gray level values. n the

gure shown above , these vertically ranging values have been quantized into E

di>erent levels or partitions. 2anging from ( blac$ to * white. This level couldvary according to the type of image you want.


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The relation of quantization with gray levels has been further discussed below.

2elation of Cuantization with gray level resolutionA

The quantized gure shown above has E di>erent levels of gray. t means that

the image formed from this signal , would only have E di>erent colors. t would

be a blac$ and white image more or less with some colors of gray. @ow if you

were to ma$e the quality of the image more better, there is one thing you can do

here. Which is , to increase the levels , or gray level resolution up. f you increase

this level to EF, it means you have an gray scale image. Which is far better then

simple blac$ and white image.

@ow EF , or E or what ever level you choose is called gray level. 2emember the

formula that we discussed in the previous tutorial of gray level resolution which

is

We have discussed that gray level can be dened in two ways. Which were these

two.

6ray level G number of bits per pi+el 5H!!).5$ in the equation)

6ray level G number of levels per pi+el.

n this case we have gray level is equal to EF. f we have to calculate thenumber of bits , we would simply put the values in the equation. n case of

EFlevels , we have EF di>erent shades of gray and bits per pi+el, hence the

image would be a gray scale image.

High-pass filter& high-pass lter is an electronic lter that passes signals with a frequency

higher than a certain cuto> frequency and attenuates signals with frequencies

lower than the cuto> frequency. The amount of attenuation for each frequency

depends on the lter design. & high-pass lter is usually modeled as a lineartime-invariant system. t is sometimes called a low-cut lter or bass-cut lter.I'J


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0igh-pass lters have many uses, such as bloc$ing 1" from circuitry sensitive to

non-zero average voltages or radio frequency devices. They can also be used in

conjunction with a low-pass lter to produce a bandpass lter.

mage

0igh-pass and low-pass lters are also used in digital image processing to

perform image modications, enhancements, noise reduction, etc., using designs

done in either the spatial domain or the frequency domain.IFJ

& high-pass lter, if the imaging software does not have one, can be done by

duplicating the layer, putting a gaussian blur, inverting, and then blending with

the original layer using an opacity 5say E(K) with the original layer.ILJ

The unsharp mas$ing, or sharpening, operation used in image editing software is

a high-boost lter, a generalization of high-pass.

& high pass lter is the basis for most sharpening methods. &n image is

sharpened when contrast is enhanced between adjoining areas with little

variation in brightness or dar$ness 5see #harpening an mage for more detailed

information).

& high pass lter tends to retain the high frequency information within an imagewhile reducing the low frequency information. The $ernel of the high pass lter is

designed to increase the brightness of the center pi+el relative to neighboring

pi+els. The $ernel array usually contains a single positive value at its center,

which is completely surrounded by negative values. The following array is an

e+ample of a M by M $ernel for a high pass lterA

Low-pass filter

& low-pass lter is a lter that passes signals with a frequency lower than a

certain cuto> frequency and attenuates signals with frequencies higher than the

cuto> frequency. The amount of attenuation for each frequency depends on thelter design. The lter is sometimes called a high-cut lter, or treble cut lter in


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audio applications. & low-pass lter is the opposite of a high-pass lter. & band-

pass lter is a combination of a low-pass and a high-pass lter.

erent forms, including electronic circuits 5such

as a hiss lter used in audio), anti-aliasing lters for conditioning signals prior to

analog-to-digital conversion, digital lters for smoothing sets of data, acoustic

barriers, blurring of images, and so on. The moving average operation used in

elds such as nance is a particular $ind of low-pass lter, and can be analyzed

with the same signal processing techniques as are used for other low-pass lters.

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