Image Perception

1. Image Perception Drawing hands by M.C Escher Waterfall by M.C Escher EE465: Introduction to Digital Image Processing

2. Human Eye Structure Three membranes enclose the eye: Cornea and sclera, Choroid, Retina ciliary body iris diaphragm Pupil size: 2-8mm Eye color: melanin (pigment) in iris http://en.wikipedia.org/wiki/Evolution_of_the_eye EE465: Introduction to Digital Image Processing

3. Retina • When the eye is properly focused, light from an outside object is imaged on the retina • Two classes of receptors are located over the surface of retina: cones and rods • Cone: 6-7 million in each eye, central part of retina (fovea) and highly sensitive to color • Rod: 75-150 million, all over the retina surface and sensitive to low levels of illumination EE465: Introduction to Digital Image Processing

4. Rods and Cones in Retina Q: Can you see a traffic light turn green while looking away from it? EE465: Introduction to Digital Image Processing

5. Image Formation in the Eye Length of tree image2.55mm Focal length: 14-17mm For distant objects (>3m), lens exhibits the least refractive power (flattened) For nearby objects (<1m), lens is most strongly refractive (curved) Q: What if the image is focused in one eye but not the other (i.e., lazy eye)? http://en.wikipedia.org/wiki/Amblyopia EE465: Introduction to Digital Image Processing

6. Lightness Perception: Objective Quantities • Luminance is the amount of visible light that comes to the eye from a surface. • Illuminance is the amount of light incident on a surface. • Reflectance (also called albedo) is the proportion of incident light that is reflected from a surface. • varies from 0% to 100% where 0% is ideal black and 100% is ideal white. In practice, typical black paint is about 5% and typical white paint about 85%. http://www-bcs.mit.edu/people/adelson EE465: Introduction to Digital Image Processing

7. Image Formation Model f(x,y)=i(x,y)r(x,y) 0<f(x,y)<∞ luminance – proportional to energy radiated by a physical source 0<i(x,y)<∞ Illumination/shading 0<r(x,y)<1 reflectance (“intrinsic images”) EE465: Introduction to Digital Image Processing

8. Example f(x,y) r(x,y) i(x,y) Q: How to separate r(x,y) and i(x,y) from f(x,y)? (Google “intrinsic images”) EE465: Introduction to Digital Image Processing

9. Lightness Perception: Subjective Quantities • Lightness is the perceivedreflectance of a surface. It represents the visual system's attempt to extract reflectance based on the luminance in the scene. • Brightness is the perceived intensity of light coming from the image itself, rather than any property of the portrayed scene. Brightness is sometimes defined as perceived luminance. EE465: Introduction to Digital Image Processing

10. Checker-block Illustration Patches p and q have the same reflectance, but different luminances. Patches q and r have different reflectances and different luminances; they share the same illuminance. 90 Patches p and r happen to have the same luminance, because the lower reflectance of p is counterbalanced by its higher illuminance. 0.1 0.9 10 0.9 0.1 EE465: Introduction to Digital Image Processing

11. Photography Illustration Q1: Do a and b have same lightness (perceived reflectance)? Q2: Do and b have same brightness (perceived luminance)? a A b Q3: Do A and B have different lightness (perceived reflectance)? Q4: Do A and B have different brightness (perceived luminance)? B Answers: YNYN EE465: Introduction to Digital Image Processing

12. Lightness Constancy Problem Recall: Image Formation Model f(x,y)=i(x,y)r(x,y) 90 10 10 0.1 0.1 0.9 p q r 9 1 9 If E(x,y) and R(x,y) are arbitrary functions, then for any E(x,y) there exists an R(x,y) that produces the observed image. The problem appears impossible, but humans do it pretty well. How do we do it? (not completely known yet, only partial explanation) “Illuminance and reflectance images are not arbitrary functions. They are constrained by statistical properties of the world.” - Land and McCann EE465: Introduction to Digital Image Processing

13. Importance of Visual Context Importance of edges Importance of corners EE465: Introduction to Digital Image Processing

14. Lightness Illusion If we cover the right side of the figure and view the left side, it appears that the stripes are due to paint (reflectance). If we cover the left side and view the right, it appears that the stripes are due to different lighting on the stair steps (illumination). EE465: Introduction to Digital Image Processing

15. Another Lightness Illusion You will verify that A and B have exactly the same value in CA3. EE465: Introduction to Digital Image Processing

16. Brightness Adaptation* Human visual system cannot operate over such a high dynamic range simultaneously, But accomplish such large variation by changes in its overall sensitivity, a phenomenon called “brightness adaptation” EE465: Introduction to Digital Image Processing

17. Mach Bands EE465: Introduction to Digital Image Processing

18. Brightness Discrimination* Weber ratio=I/I EE465: Introduction to Digital Image Processing

19. Simultaneous Contrast Same luminance but varying brightness (perceived luminance) EE465: Introduction to Digital Image Processing

20. Optical Illusions EE465: Introduction to Digital Image Processing