DIP_Slides 2 Image Fundamentals_ Umer Javed

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I I U I

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CS-407: Digital Image Processing

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C H A P T E R : 2

D I G I TA L I M A G E F U N D A M E N TA L S

CS-407: Digital Image Processing

Human Eye

Umer Javed, CS: 407: Digital Image Processing

Courtesy: DIP 3/Edition

Chapter:2, Slide # 3

Human Eye


Iris:

Controls amount of light entering in eye by contraction or expansion.

Retina:

Inner most layer

Contains 2 type of receptors

Cones

Rods


Human Eye


Cones: Exist a number of 6~7 Million in each eye.

Central Position at Fovea.

Highly sensitive to color.

Helps in resolving fine details.

Cone vision is known as Phototopic or Bright light vision.

Rods: 75~150 Million, Residing all over retina

Reduce Amount of detail.

Creates general overview of picture

Sensitive to low level intensitites.

In low light, objects appear colorless, because only Rods are active.

Vision is called Scotopic or Dim Light Vision.


Human Eye

Umer Javed, CS: 407: Digital Image Processing Chapter:2, Slide # 6


Human Eye



Brightness Adaptation


Light Intensity vs

Subjective Brightness.

mL= millilambert.

In high brightness range Photopic

vision is active.

In Low Brightness range Scopic

vision is active.

Human vision system cannot operate

over such range simultaneously, rather

it adjusts its sesitivity.



Weber Ratio


Introduce bright light, , if increment is not brighter,change wont be detectable.

Smaller WB, means small change is detectable.

Larger WB, means only large change is detectable.

I

cIWeberRatio :I


Limitations of Eye



Limitations of Eye



Limitations of Eye



Electromagnetic Spectrum



Image Sensing


Single image sensor:

Incoming energy transforms into voltage by Combination of Input electrical power and sensor material.

Output voltage can be digitized.

Photodiode follows this kind of behavior.

Colored sensors give maximum voltage for similar colors and minimum for others.


Image Sensing

Chapter:2, Slide # 15Umer Javed, CS: 407: Digital Image Processing

Sensor Strips:


Image Sensing


Sensor Arrays:

Charged Coupled Devices (CCD)

Widely used in digital cameras

Complimentary Metal Oxide Semiconductor (CMOS)

CMOS doesn’t require charged couples

Application Areas:

Air Borne Imaging

X-Rays Scan

Computerized Axial Tomography (CAT)

Positron Emission tomography (PET)

Magnetic Resonance Imaging (MRI)


Image Formation



Image Formation


Image as a function should be positive and finitei.e.

Two key components play their role

Amount of source illumination, incident

Amount of source illumination, reflected

Function results in


0 < f(x, y)<

i(x, y)

r(x, y)

0 <i(x, y)<

0 < r(x, y)<1

f(x, y)= i(x, y)r(x, y)

Intensity Measures


Image intensity/gray scale as a functioni.e.

Intensity ranges

Where

Gray Scale Range

generally used as: OR


0 0= f(x , y )

min maxL L

min min minL = i rmax max maxL = i r

,min maxL L 0, L -1

Sampling and Quantization


Creates digital image from sensed data.

Image may be continuous w.r.t x, y-axis and amplitude .

Sampling:

Digitizing the Coordinate values.

Equally spaced samples taken for Figure 2.16.

Practically, Sampling depends upon sensor arrangement.

Quantization:

Digitizing the Amplitude values.

8 Level quantization is performed on Figure 2.16.








Digital Image Values

Introduction 23Umer Javed, CS: 407: Digital Image Processing


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DIP_Slides 2 Image Fundamentals_ Umer Javed