Dip u1_digital Image Fundamentals

DIGITAL IMAGE PROCESSING

G.Arumugam. L/ECE.G.Arumugam. L/ECE.Sasurie Academy of Engineering.Sasurie Academy of Engineering.

THIS SESSION…..

1. Basic Discussion About the Subject….2. Unit -1 [ Digital Image Fundamentals]

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WHY ? DIGITAL IMAGE PROCESSING

“One picture is worth more than thousand

words”

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IMAGE PROCESSING – (AN APPLICATION VIEW)

Satellite images.

(GPS , Agriculture , Military Applications )

Biomedical images. (Cancer Detection, Tumor

Detection.)

Industrial Automation. (Finding the Discontinuities)

Robotics. Remote Sensing.

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IMAGEImage

Reflection of Light from an object representing as a 2D function f(x,y) .

(incident and reflection of light)

Digital Image Its an array of pixels that stores light intensities in

binary values. E.g.. Photograph , map ,chart.

Pixels A (2-D) grid that are often represented as dots or

squares. Each pixel is a sample of an original image. Caries and stores similar or variable intensity levels.

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CLASSIFICATION OF DIGITAL IMAGES

BINARY IMAGE Binary refers two. The Entire Image is represented by only two levels of

Intensities

0 – Black

1 – White

Black – 0

White – 16

For an 8-bit image the intensity levels varies from 0 to 255.

0- Black

255- White

In between range represent's gray levels

8-bit image – Each pixel carries 8 no of zeros (0000 0000) for black and 8 no of ones (1111 1111) for 255.

2n – n represents no of bits in one pixel. n = 8 then 28= 256 (i.e.) 0 to 255 n = 16 then 216=65,536 (i.e.) 0 to 65,535

CLASSIFICATION OF DIGITAL IMAGES

GRAY SCALE IMAGE

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GRAY SCALE IMAGE

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Each pixel of a color image carries 24- bits to represent the primary colors.

Red – 8 bits Green – 8 bits Blue – 8 bits 224=16 777 216

CLASSIFICATION OF DIGITAL IMAGES

COLOR IMAGE

16 777 216 range of colors

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COLOR IMAGE

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CLASSIFICATION OF DIGITAL IMAGES

Binary Gray Scale Color

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UNIT-1 DIGITAL IMAGE FUNDAMENTALS

Topics to be Discussed Elements of digital image processing systems. Elements of visual perception. Psycho visual model- brightness- contrast- hue-

saturation. Mach band effect. Color image fundamentals - RGB- HSI models. Image sampling- Quantization. Dither. Two dimensional mathematical preliminaries .

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Elements of digital image processing systems. Elements of visual perception. Psycho visual model- brightness- contrast- hue- saturation. Mach band effect. Color image fundamentals - RGB- HSI models. Image sampling- Quantization. Dither. Two dimensional mathematical preliminaries .

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ELEMENTS OF DIGITAL IMAGE PROCESSING SYSTEMS

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Elements of digital image processing systems.

Elements of visual perception. Psycho visual model- brightness- contrast- hue- saturation. Mach band effect. Color image fundamentals - RGB- HSI models. Image sampling- Quantization. Dither. Two dimensional mathematical preliminaries .

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ELEMENTS OF VISUAL PERCEPTION.

Structure of eye Image formation in eye Brightness Adaptation and Discrimination.

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Structure of eye Image formation in eye Brightness Adaptation and Discrimination.

ELEMENTS OF VISUAL PERCEPTION.

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STRUCTURE OF EYE

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Eye is nearly sphere in shape of average diameter 20mm. Three important membranes are

1. Cornea and Sclera

2. Choroid

3. Retina Cornea - Transparent tissue that covers the anterior surface of the

eye. Sclera - Encloses the remaining part. Choroid – Responsible for nutrition of eye. Retina – Light from the object is imaged in retina , contains two

receptors

Cones and Rods. Iris – controls the amount of light entering the eye ( diameter 2 to 8

mm). Lens – contains 60 to 70 % of water and 6% fat. Absorbs approx. 8%

of visible light19

Cones 6 to 7 millions . Deposited at the centre portion of retina

(fovea). Highly sensitive to color. Each cone is connected with its own nerve end. Cone vision is Photopic or Bright Light Vision.

Rods 75 to 150 millions. Spread over the retinal region. Rod vision is Scotopic or Dim Light Vision.

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DISTRIBUTION OF CONES AND RODS

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Structure of eye

Image formation in eye Brightness Adaptation and Discrimination.

ELEMENTS OF VISUAL PERCEPTION.

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IMAGE FORMATION IN THE EYE

15 / 100 = h / 17

h = 2.55mm23

Structure of eye Image formation in eye

Brightness Adaptation and Discrimination.

ELEMENTS OF VISUAL PERCEPTION.

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BRIGHTNESS ADAPTATION

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BRIGHTNESS DISCRIMINATION.

K

I

K

I

K

I

I- Light illumination in Square

K- Light illumination in Circle

I = K I ≤ K

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Elements of digital image processing systems. Elements of visual perception. Psycho visual model- brightness- contrast- hue- saturation.

Mach band effect. Color image fundamentals - RGB- HSI models. Image sampling- Quantization. Dither. Two dimensional mathematical preliminaries .

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MACHBAND EFFECT

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SIMULTANEOUS CONTRAST

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OPTICAL ILLUSION

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Elements of digital image processing systems. Elements of visual perception.

Psycho visual model- brightness- contrast- hue- saturation.

Mach band effect. Color image fundamentals - RGB- HSI models. Image sampling- Quantization. Dither. Two dimensional mathematical preliminaries .

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Hue- Dominant wavelength in a mixture of light waves (i.e Purest form of color)

Saturation - Amount of white light mixed with hue.

Brightness - Subjective Descriptor cannot be measurable varies for individuals.

Contrast – Adding same color.

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Elements of digital image processing systems. Elements of visual perception. Psycho visual model- brightness- contrast- hue- saturation. Mach band effect.

Color image fundamentals - RGB- HSI models.

Image sampling- Quantization. Dither. Two dimensional mathematical preliminaries .

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COLOR IMAGE FUNDAMENTALS

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ELECTROMAGNETIC SPECTRUM

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Achromatic - Void of color, Light in black and white TV Chromatic - Color light spectrum from approx. 400 to 700 nm. Quality of chromatic light• Radiance - Total amount of energy that flows from the light

source.

Unit-watts (w) • Luminance - Amount of energy absorb from the light source.

Unit- lumens (ls)• Brightness - Subjective Descriptor cannot be measurable Cone sensors are responsible for color vision 65% RED (700nm) 33% GREEN (546.1nm) 2% BLUE (485.8nm)

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SPECTRAL RESPONSE OF CONES

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Primary: RED GREEN BLUE

Secondary: MAGENTA YELLOW CYAN

Primary: MAGENTA YELLOW CYANSecondary: RED GREEN BLUE

MIXTURE OF COLOR LIGHT

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RGB COLOR MODEL

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RGB COLOR CUBE

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HSI COLOR MODEL

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Elements of digital image processing systems. Elements of visual perception. Psycho visual model- brightness- contrast- hue- saturation. Mach band effect. Color image fundamentals - RGB- HSI models.

Image sampling- Quantization. Dither. Two dimensional mathematical preliminaries .

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ANALOG & DIGITAL IMAGE

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IMAGE SAMPLING AND QUANTIZATION

Digitizing the co ordinate values is called Sampling

Digitizing the amplitude values is called Quantization

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Elements of digital image processing systems. Elements of visual perception. Psycho visual model- brightness- contrast- hue- saturation. Mach band effect. Color image fundamentals - RGB- HSI models. Image sampling- Quantization.

Dither. Two dimensional mathematical preliminaries .

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DITHER

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DISCUSSIONS ??

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Thank You

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