digital image processing part 1 introduction. the eye

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Digital Image Processing Part 1 Introduction

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Page 1: Digital Image Processing Part 1 Introduction. The eye

Digital Image Processing

Part 1

Introduction

Page 2: Digital Image Processing Part 1 Introduction. The eye

The eye

Page 3: Digital Image Processing Part 1 Introduction. The eye

The eye

• Retina is covered by photoreceptors: cones and rods • Fovea contains cones only (most vision here)• Outside fovea, the retina is mostly covered by rods

• Cones: primarily color perception• Long - more sensitive to long wavelength (red)• Medium - more sensitive to medium wavelength (green)• Short - more sensitive to short wavelength (blue)

• Rods: highly sensitive to intensity and black/white vision, responsible for vision under dark-dim condition

Page 4: Digital Image Processing Part 1 Introduction. The eye

Receptor distribution

• High density cones around 0 (1.5 mm)• Some rods in fovea but most outside• About 6 – 7 million cones, 75 – 150 million rods

Page 5: Digital Image Processing Part 1 Introduction. The eye

Test Blind Spot

• Cover one eye

• Focus on the X and move closer to the screen

• The spot eventually becomes invisible but moving closer still enables you to see it again

Page 6: Digital Image Processing Part 1 Introduction. The eye

Visible light

Page 7: Digital Image Processing Part 1 Introduction. The eye

Colour perception

There is no colour in light but the stimulation of the rods and cones by specific frequencies creates a visual representation of colour in the brain

Red receptors cover a significant portion of the green band. Green is perceived more strongly than red and both more than blue

Perception is around: 0.59G, 0.3R and 0.11B

Page 8: Digital Image Processing Part 1 Introduction. The eye

Colour blindness

• Defective X chromosome

• Men have XY women have XX so higher probability of having one good X

• 8% of males are red / green colour blind

• Women may be able to detect subtle red green differences better through combination of XX

Page 9: Digital Image Processing Part 1 Introduction. The eye

Colour blindness test 1

Page 10: Digital Image Processing Part 1 Introduction. The eye

Colour blindness test 2

Page 11: Digital Image Processing Part 1 Introduction. The eye

Colour blindness test 3

Page 12: Digital Image Processing Part 1 Introduction. The eye

Camera and Eye comparison

Page 13: Digital Image Processing Part 1 Introduction. The eye

Image Sensor Operation

• Charge Coupled Device image sensor

• Background is image sensor zoomed in

• CCD measures brightness• Tiny lenses direct light onto filtered

photosensitive regions• More green than red to better match the eye

Page 14: Digital Image Processing Part 1 Introduction. The eye

Bayer filter

• Eye responds mostly to green so as many green filters as red+blue

• Demosaic – interpolate a single pixel colour by interpolating nearest neighbours as each pixel only records one colour so the actual colour at that point is the average if it and the surrounding pixels

Page 15: Digital Image Processing Part 1 Introduction. The eye

CCD Operation

Page 16: Digital Image Processing Part 1 Introduction. The eye

CCD Operation

• Charge is moved down 1 row at a time then clocked out to an amp and A to D converter

Page 17: Digital Image Processing Part 1 Introduction. The eye

Colour models

• Additive – light, e.g. Computer Monitor– Primary: Red, Green, Blue– Secondary: R+G=Y, B+R=M, B+G=C– R+G+B = White

• Subtractive – pigment e.g. printer– Primary: Yellow, Magenta, Cyan– Secondary: R,G,B– Y+M+C = Black

Page 18: Digital Image Processing Part 1 Introduction. The eye

Colour Properties

• Hue (color of the light - dominant frequency)

• Brightness – perceived intensity of the light

• Saturation (purity) – a measure of the degree to which a pure color is diluted by white light

• Chromaticity refers to Hue and Saturation

Page 19: Digital Image Processing Part 1 Introduction. The eye

Monitor & Printer Colour Models

Page 20: Digital Image Processing Part 1 Introduction. The eye

RGB colour cube

Page 21: Digital Image Processing Part 1 Introduction. The eye

HIS Model (human model)

Page 22: Digital Image Processing Part 1 Introduction. The eye

HSI Conversion

• Hue, Saturation and Intensity are separated

• Several operations work on intensity only so this model is ideal for them (luminance or grey level). For example, brightness and contrast modification

• Converting RGB to I is trivial: I=(R+B+G)/3

• H and S are not trivial

Page 23: Digital Image Processing Part 1 Introduction. The eye

Grey Scale

Page 24: Digital Image Processing Part 1 Introduction. The eye

Sampling

Page 25: Digital Image Processing Part 1 Introduction. The eye

Sampled image

Page 26: Digital Image Processing Part 1 Introduction. The eye

Brightness and Contrast

• Grey scale and histogram of pixel values

Page 27: Digital Image Processing Part 1 Introduction. The eye

Dark and Light Images

Page 28: Digital Image Processing Part 1 Introduction. The eye

Low Contrast

To lighten or darken, shift the distribution left or right

To increase contrast, stretch the distribution over a wider range

Page 29: Digital Image Processing Part 1 Introduction. The eye

Good Contrast

• Almost full dynamic range used. Could contrast stretch slightly

Page 30: Digital Image Processing Part 1 Introduction. The eye

Point Processing - Brightness

• Map current pixel values into new values. Useful for brightness, contrast, posterise and threshold.

Page 31: Digital Image Processing Part 1 Introduction. The eye

Brightness adjustment• To increase brightness, add or subtract

constant from each pixel colour value

• Need to clamp at MAX (255) and MIN (0)

Convert to greyscale• Produce mean brightness levels:• Multiply each pixel colour value by:

0.59xGreen, 0.11xBlue and 0.3xRed• Need to clamp at MAX (255) and MIN (0)

Page 32: Digital Image Processing Part 1 Introduction. The eye

Point process contrast