Digital Image Processing Part 1 Introduction. The eye

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

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

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

Visible light

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

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

Colour blindness test 1

Colour blindness test 2

Colour blindness test 3

Camera and Eye comparison

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

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

CCD Operation

CCD Operation

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

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

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

Monitor & Printer Colour Models

RGB colour cube

HIS Model (human model)

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

Grey Scale

Sampling

Sampled image

Brightness and Contrast

• Grey scale and histogram of pixel values

Dark and Light Images

Low Contrast

To lighten or darken, shift the distribution left or right

To increase contrast, stretch the distribution over a wider range

Good Contrast

• Almost full dynamic range used. Could contrast stretch slightly

Point Processing - Brightness

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

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)

Point process contrast