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CM20219: Visual Computing > Lecture 3/4 Display tech / Image formation and filtering > Flashcards

Lecture 3/4 Display tech / Image formation and filtering Flashcards

1
Q

Why is a barrier needed between an object and film in a pin-hole camera?

A

To control the rays of light from the object
Only allowing light to enter through a pin-hole aperture.

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2
Q

Dimensionality Reduction Machine (?? to ??)
What does this machine accomplish?

A

Convert the 3D world to a 2D image

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3
Q

How does a large aperture affect an image?

A

Blurry and bright image

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4
Q

How will having a tiny aperture affect an image?

A

Too small an aperture will create a blurry and dark image

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5
Q

What does a lens do to an image?

A

A lens focuses parallel rays of light onto film
- Objects focus at a distance of f
- Other points project to a “circle of confusion” in the image
- Changing the shape of the lens changes the focal distance

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6
Q

How does focal distance relate to object and image distance?

A

f: focal distance
u: object distance
v: image distance

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7
Q

What shape does a lens take?

A

Lenses are typically spherical - this is easier to produce

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8
Q

What is D?

A

The aperture of diameter D restricts the range of rays
- aperture may be on either side of the lens

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9
Q

What is f?

A

The focal point is at a distance f beyond the plane of the lens
- f is a function of the shape and index of refraction of the lens

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10
Q

What are the effects of changing the aperture size?

A

Changing the aperture size affects the depth of field
- A smaller aperture increases the range in which the object is approximately in focus

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11
Q

Compare a camera to the human eye

A

Iris - colored annulus with radial muscles
Pupil - the hole (aperture) whose size is controlled by the iris

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12
Q

What’s the “film” equivalent in an eye?

A

photoreceptor cells (rods and cones) in the retina

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13
Q

What does this image (from a sensor array) show?

A

A continuous image projected onto a sensor array

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14
Q

What does this image (from a sensor array) show?

A

Result of image sampling and quantisation

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15
Q

How does a sensor array record light?

A

▪ turn continuous light into pixels
▪ cells detect photons (as electrons)
over an array of pixels

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16
Q

What is a CCD?

A

Stands for Charge Coupled Device. A type of image sensor.
They are serial devices where pixels
are read out one at a time.

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17
Q

What is a CMOS?

A

A type of image sensor.
each pixel contains an
amplifier, so read-out can be faster (than a CCD)

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18
Q

Why are there different image sensor types, what are they?

A

Different sensor types use different
approaches to read out electrons.
CCD - pixels read out 1 by 1
CMOS - each pixel contains an amplifier… faster read-out

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19
Q

What are the active image display technologies?

A

LCD - Liquid Crystal Display
Digital Mirror Displays
OLED
Plasma Displays
Cathode Ray Tube

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20
Q

What are passive image display technologies?

A

PRINTERS:
Laser printers
ink-jet printers
Commercial printers

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21
Q

What active image display is most common today?

A

LCD - Liquid Crystal Display

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22
Q

What active image display was standard for most of the 20th century?

A

Cathode Ray Tube

23
Q

What are OLEDs used for?

A

Expensive high end devices.
Emit RGB no need for a back light (like LCDs)

24
Q

What is a negative of plasma displays?

A

They’re power-hungry.
They were briefly popular.

25
Q

How do LCDs work?

A

liquid crystals twist the
polarisation of light
- voltage across the liquid crystal
controls how much light
passes:
– voltage on: no light
(crystals align the electric field)
– Voltage off: maximum light
(crystals align to each other,
smoothly twisting light)

26
Q

How is light controlled when voltage is ON in an LCD display?

A

ON = No light
crystals align with the electric field

27
Q

How is light controlled when voltage is OFF in an LCD display?

A

OFF = Maximum light
crystals align to each other,
smoothly twisting light

28
Q

How does the effect of quantisation vary as the bit number is increased?

A

More continuous and detailed image with more bits

29
Q

How many bits (colour depth) are
needed in a qunatised image?

A
30
Q

What does error diffusion achieve

A

Error diffusion achieves visually more pleasing results by distributing
quantisation errors across neighbouring pixels

31
Q

How would you increase the brightness of an image?

A

Increase the value of each pixel by a fixed amount such that all pixel values are equal to or less than 255 (max)

32
Q

In per pixel processing what is the image inversion equation?

A

Inverted Image

33
Q

In per pixel processing what is the contrast enhancing equation?

A
34
Q

What are these point-based filter maps showing?

A

Darkening and lightning

35
Q

What are these point-based filter maps showing?

A

High and low contrast

36
Q

What are these point-based filter maps showing?

A

Compressed to darks and compressed to lights

37
Q

What are these point-based filter maps showing?

A

Emphasise shadows and lights

38
Q

What are point-based filters?

A

These filters operate on a per-pixel basis.

They involve applying a function to each pixel of an image individually, based on the value of that pixel.

Common point-based filters: linear, median, and convolutional filters.

39
Q

What are the limitations of a point-based filter?

A

Limited ability to capture structure and context: causes degraded image quality or loss of important image features.

Sensitivity to noise: result in the amplification of noise and degraded image quality.

Limited control: they apply a fixed function to each pixel. This can make it difficult to fine-tune the processing.

Over- or under-processing: unnatural or distorted appearance.

40
Q

How to overcome noise in point-based filters?

A

Use neighbourhood filters

41
Q

What filter can be applied to an image to remove salt and pepper noise?

A

Median filter: this will replace each pixel with the median value of all pixels in
its neighborhood. NOT A CONVOLUTION FILTER

42
Q

What is the difference between correlation and convolution?

A

Convolution is
correlation with the
kernel rotated 180°

43
Q

In a morphological filter, we can obtain erosion of a pixel using the following formula

A
44
Q

In a morphological filter, we can obtain the dilation of a pixel using the following formula

A
45
Q

In a morphological filter describe Opening

A

DILATION AFTER EROSION

46
Q

In a morphological filter describe Closing

A

EROSION AFTER DILATION

47
Q

What are examples of sobel filters?

A

Horizontal gradients
Vertical gradients
Diagonal gradients

48
Q

What does a sobel filter kernel look like for:
Horizontal gradients

A
49
Q

What does a sobel filter kernel look like for:
Vertical gradients

A
50
Q

What does a sobel filter kernel look like for:
Diagonal gradients

A
51
Q

Show equation for a gaussian (low pass) filter

A
52
Q

What are the fundamental differences between a box filter and a gaussian filter?

A

Box filter gives equal weight to all pixels
Gaussian trusts the center pixel more

53
Q

Visualise a kernel for
A motion blur convolution filter

A
54
Q

Visualise the convolution kernel:

Sharpening using unsharp masking

A

CM20219: Visual Computing (10 decks)

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