Recap from Friday Pinhole camera model Perspective projections Lenses and their flaws Focus Depth of field Focal length and field of view

Recap from Friday

Pinhole camera model

Perspective projections

Lenses and their flaws

Focus

Depth of field

Focal length and field of view

What is wrong with this picture?

What is wrong with this picture?

Capturing Light… in man and machine

CS 195g: Computational PhotographyJames Hays, Brown, Spring 2010

Many slides by Alexei A. Efros

Image Formation

Digital Camera

The Eye

Film

Digital camera

A digital camera replaces film with a sensor array• Each cell in the array is light-sensitive diode that converts photons to electrons• Two common types

– Charge Coupled Device (CCD) – CMOS

• http://electronics.howstuffworks.com/digital-camera.htm

Slide by Steve Seitz

http://electronics.howstuffworks.com/digital-camera.htm

Sensor Array

CMOS sensor

Sampling and Quantization

Interlace vs. progressive scan

http://www.axis.com/products/video/camera/progressive_scan.htm Slide by Steve Seitz

http://www.axis.com/products/video/camera/progressive_scan.htm

Progressive scan



Interlace



The Eye

The human eye is a camera!• Iris - colored annulus with radial muscles

• Pupil - the hole (aperture) whose size is controlled by the iris

• What’s the “film”?– photoreceptor cells (rods and cones) in the retina


The Retina

Cross-section of eye

Ganglion cell layer

Bipolar cell layer

Receptor layer

Pigmentedepithelium

Ganglion axons

Cross section of retina

Retina up-close

Light

© Stephen E. Palmer, 2002

Cones cone-shaped less sensitive operate in high light color vision

Two types of light-sensitive receptors

cone

rod

Rods rod-shaped highly sensitive operate at night gray-scale vision

Rod / Cone sensitivity

The famous sock-matching problem…


Distribution of Rods and Cones.

0

150,000

100,000

50,000

020 40 60 8020406080

Visual Angle (degrees from fovea)

Rods

Cones Cones

Rods

FoveaBlindSpot

# R

ecep

tors

/mm

2

Night Sky: why are there more stars off-center?

Eye Movements

Saccades

Microsaccades

Ocular microtremor (OMT)

Electromagnetic Spectrum

http://www.yorku.ca/eye/photopik.htm

Human Luminance Sensitivity Function

Why do we see light of these wavelengths?


.

0 1000 2000 3000

En

erg

y

Wavelength (nm)

400 700

700 C

2000 C

5000 C

10000 C

VisibleRegion

…because that’s where theSun radiates EM energy

Visible Light

The Physics of Light

Any patch of light can be completely describedphysically by its spectrum: the number of photons (per time unit) at each wavelength 400 - 700 nm.

400 500 600 700

Wavelength (nm.)

# Photons(per ms.)



.

# P

ho

ton

s

D. Normal Daylight

Wavelength (nm.)

B. Gallium Phosphide Crystal

400 500 600 700

# P

ho

ton

s

Wavelength (nm.)

A. Ruby Laser

400 500 600 700

400 500 600 700

# P

ho

ton

s

C. Tungsten Lightbulb

400 500 600 700

# P

ho

ton

s

Some examples of the spectra of light sources



Some examples of the reflectance spectra of surfaces

Wavelength (nm)

% P

hoto

ns R

efle

cted

Red

400 700

Yellow

400 700

Blue

400 700

Purple

400 700


The Psychophysical Correspondence

There is no simple functional description for the perceivedcolor of all lights under all viewing conditions, but …...

A helpful constraint: Consider only physical spectra with normal distributions

area

Wavelength (nm.)

# Photons

400 700500 600

mean

variance



Mean Hue

yellowgreenblue

# P

hoto

ns

Wavelength



Variance Saturation

Wavelength

high

medium

low

hi.

med.

low# P

hoto

ns



Area Brightness#

Pho

tons

Wavelength

B. Area Lightness

bright

dark



.

400 450 500 550 600 650

RE

LAT

IVE

AB

SO

RB

AN

CE

(%

)

WAVELENGTH (nm.)

100

50

440

S

530 560 nm.

M L

Three kinds of cones:

Physiology of Color Vision

• Why are M and L cones so close?• Why are there 3?

More Spectra

metamers

Color Sensing in Camera (RGB)

3-chip vs. 1-chip: quality vs. cost

Why more green?

http://www.cooldihttp://www.cooldictionary.com/words/Bayer-filter.wikipediationary.com/words/Bayer-filter.wikipedia

Why 3 colors?


Practical Color Sensing: Bayer Grid

Estimate RGBat ‘G’ cells from neighboring values

http://www.cooldictionary.com/words/Bayer-filter.wikipedia


RGB color space

RGB cube• Easy for devices• But not perceptual• Where do the grays live?• Where is hue and saturation?


HSV

Hue, Saturation, Value (Intensity)• RGB cube on its vertex

Decouples the three components (a bit)Use rgb2hsv() and hsv2rgb() in Matlab


Project #1

• How to compare R,G,B channels?• No right answer

• Sum of Squared Differences (SSD):

• Normalized Correlation (NCC):

Image half-sizing

This image is too big tofit on the screen. Howcan we reduce it?

How to generate a half-sized version?

Image sub-sampling

Throw away every other row and

column to create a 1/2 size image- called image sub-sampling

1/4

1/8


Image sub-sampling

1/4 (2x zoom) 1/8 (4x zoom)

Aliasing! What do we do?

1/2


Gaussian (lowpass) pre-filtering

G 1/4

G 1/8

Gaussian 1/2

Solution: filter the image, then subsample• Filter size should double for each ½ size reduction. Why?


Subsampling with Gaussian pre-filtering

G 1/4 G 1/8Gaussian 1/2


Compare with...

1/4 (2x zoom) 1/8 (4x zoom)1/2


Gaussian (lowpass) pre-filtering

G 1/4

G 1/8

Gaussian 1/2

Solution: filter the image, then subsample• Filter size should double for each ½ size reduction. Why?• How can we speed this up? Slide by Steve Seitz

Image Pyramids

Known as a Gaussian Pyramid [Burt and Adelson, 1983]

• In computer graphics, a mip map [Williams, 1983]• A precursor to wavelet transform


A bar in the big images is a hair on the zebra’s nose; in smaller images, a stripe; in the smallest, the animal’s nose

Figure from David Forsyth

What are they good for?

Improve Search• Search over translations

– Like project 1

– Classic coarse-to-fine strategy

• Search over scale– Template matching

– E.g. find a face at different scales

Pre-computation• Need to access image at different blur levels• Useful for texture mapping at different resolutions (called

mip-mapping)

Gaussian pyramid construction

filter mask

Repeat• Filter• Subsample

Until minimum resolution reached • can specify desired number of levels (e.g., 3-level pyramid)

The whole pyramid is only 4/3 the size of the original image!Slide by Steve Seitz

Documents

Recap from Friday Pinhole camera model Perspective projections Lenses and their flaws Focus Depth of field Focal length and field of view