1. Digital Image Processing Part 1 Introduction

2. The eye

3. 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

4. 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

5. 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

6. Visible light

7. 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

8. 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

9. Colour blindness test 1

10. Colour blindness test 2

11. Colour blindness test 3

12. Camera and Eye comparison

13. 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

14. 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

15. CCD Operation

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

17. 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

18. 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

19. Monitor & Printer Colour Models

20. RGB colour cube

21. HIS Model (human model)

22. 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

23. Grey Scale

24. Sampling

25. Sampled image

26. Brightness and Contrast Grey scale and histogram of pixel values

27. Dark and Light Images

28. Low Contrast To lighten or darken, shift the distribution left or right To increase contrast, stretch the distribution over a wider range

29. Good Contrast Almost full dynamic range used. Could contrast stretch slightly

30. Point Processing - Brightness Map current pixel values into new values. Useful for brightness, contrast, posterise and threshold.

31. 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)

32. Point process contrast