Section 1: Imaging and signalling Flashcards
What does a wave do?
A progressive (moving) wave carries energy and usually information from one place to another without transferring material.
Frequency and period link
Frequency = 1/period
Wavespeed, freq and wavelength equation
v=frequency x wavelength
Intensity of waves
Intensity is a measure of how much energy each wave carries
measured in Watts per square metre (Wm^-2)
Intensity = Power/Area
Give 5 examples of how waves can be used to generate images
Sight- visible light waves hitting retinas and trnsferring an image
Medical scanning- E.g Ultrasound scans build up an image by detecting reflected ultrasound waves
Heat cameras- sense infrared waves being emitted by the object being observed. also the same type of wave carries signal from tv remote to tv
Remote sensing- Satellites use sensors to detect waves from distant objects to do things such as keep track of vegetation, whether or make accurate elevation maps
Communications - mobile phones send and receive microwaves that carry signal containing information sent from your phone.
Difference between a polarised and non-polarised wave.
Waves that are vibrating on more than one plane are referred to as non-polarised waves
A polarised wave is a wave that only oscillates in one direction or only vibrates in one plane.
Electromagnetic polarisation
Electromagnetic radiation is made up of two types of transverse wave, the vibrations are in electric and magnetic fields.
Polarising filter acts like a fence, light that passes through will only be vibrating in one direction
two polarising filters at right angles
No waves will pass through
Which type of waves do polarisation filters work on
Polarisation filters only work on transverse waves.
This is one indication that light is a transverse wave as it can be polarised.
Investigating the polarisation of light
- Align transmission axis of both filters so they are both vertical, keep position of 1st filter fixed
- light is always vertically polarised coming through the first filter
- when two filters are aligned all light passes through
-as rotate the 2nd, the light that passes through varies
(think of filters as vectors having vertical and horizontal component, the larger the vertical component the more vertical light) - when full transmission axis are at 45 degrees to each other half the light will shine through. At right angles no light will pass through - the intensity is 0
Polarising microwaves
Using a metal grille
- place grill between the microwave transmitter and receiver, microwave transmitters transmit polarised waves
- Intensity is a maximum when grill and direction of vibrations are at right angles to each other
- as grille is rotated, intensity decreases
- when lines and direction are aligned, no signal
Which direction should the grill be when intensity is 0
polarisation of microwaves
The intensity drops to zero, when wires are aligned with the direction of polarisation of microwaves, because the grille is absorbing their energy
How polarisation of microwaves work
- vibration electric field of microwaves excites electrons in the metal grille
- energy is absorbed by the grille and re-emitted in all directions
- only a few of the re-emitted waves are vibrating in the general direction of the microwave receiver
- the receiver only recieves waves in one plane, so even if waves travel towards it, they may not be picked up
- When wires and vibrations of waves are aligned, more electrons vibrate as they absorb vertical energy and have more room to more when grid is aligned
- when wires and vibrations are at right angles some electrons are still excited so there is a small drop in intensity
What occurs when a wave reaches a boundary in materials
Refraction
If the wave (light) meets the boundary at an angle to the normal, transmitted ray is bent or refracted as it travals at a different speed in different medium
the amount of refraction depends on the wave length of light,
(so focal length will change depending on wavelength)
What do converging lenses do?
Converging lenses change the curvature of wave-fronts by refraction.
How do converging lenses do what they do?
A converging lens adds curvature to the wave as it passes through.
They curve the wave fronts by slowing down the light travelling through the centre of the lens more than the light entering at the edges.
All points on the wave take an equal amount of time to get to the focus point.
Power and thickness relationship
The more powerful the lens is the thicker it is, the more it will curve the wave-fronts that travel through.
shorter focal length.
Lens equation
1/v = 1/u +1/f
(u is almost always negative)
curvature after = curvature before + curvature added by lens
power, and curvature equations
P= 1/f (P measured in Dioptres, D) Curvature = 1/f
Lens makers equation
1/f = (n-1)[1/R’ -1/R]
f is focal length
n is index of refraction of lens
R’ (after lens) and R (before lens) are the radii of the two sides of the two sides of lens.
what happens when 1/u =0
the lens will add a curvature of 1/f and the focus will be at the focal point
What happens if the object is at the focus point of the lens ( on the u side)
The lens will add curvature (-ve) and the waves will leave parallel to the axis of the lens. There will be no focus point/it will be at infinity
Lens magnification equation
linear magnification = image height / object height
m =v/u
Define focal length of a lens
the distance between the centre of a lens and it’s focus
Describe The experiment to determine the focal length of a thin converging lens
- set up a bulb, a lens and a screen all on the same axis will a ruler to measure the distances between them.
- place the bulb an exact distance from the lens, i.e 0.2 m so u= 0.2
move the screen until you can see a clear picture of the filament on the screen. - measure the distance between the lens and the screen with image. this is v
-Repeat - use equation to find 1/f and therefore power of lens
-find average of your values for 1/f and divide by 1 to give focal length f for your lens
What is a bit
A single binary digit is called a bit
What is a byte
A byte is a group of eight bits
How does a computer store data
As a string of bits, the number of bits in a string determines how many alternatives the string can represent.
Number of alternatives equation
Number of alternatives = 2^(number of bits)
N=2^b
Number of bits = Log base 2 (number of alternatives)
How are images stored
As an array of binary numbers
each pixel is represented by a binary number, with 1 byte and 8 bits (for b&w images)
binary numbers are stored as an array, so the location of each number refers to the location of the pixel in the photo.
The value of the number refers to the colour of the pixel
How are coloured images stored
Each pixel is described as three binary numbers.
1 byte for each primary colour ( red, blue and GREEN)
24 bits per pixel
Value of number gives colour of corresponding pixel
Image resolution definition
Image resolution is the detail an image holds.
usually refers tothe length represented by each pixel.
If an object of width 1m is represented by 200 pixels in an image then 1/200 = resolution = 0.005
smaller resolution is better
RESOLUTION CAN MEAN DIFFERENT THINGS
What does amount of info depend on? b/w and coloured
Bits per pixel
pixels range from 0-225 or 2^0 – 2^8
with 0 being black and 255 being white
colours are made up of three numbers each providing 256 possible shades of red green and blue
this means there are (2^8)^3 = 2^24 possible different colour combinations
information in image equation
total amount of info = number of pixels x bits per pixel
Manipulate brightness
Pixels are stored as a number, changing the brightness means changing the value of each pixel
adding a fixed positive value to the image makes it lighter (will shift the histogram to the right by fixed value)
Manipulating contrast
mnipulating by a fixed value greater than 1 makes the image brighter and increases the contrast (e.g. multiply every pixel by 2)
However this is flawed as the image will become significantly brighter
If all pixels were in range 50–> 150 scaling all pixels to have a range from 0–>255 will change the contrast without editing the brightness significantly
so: 50-> 0 and 150->255
Manipulate to highlight feature
Adding false colour.
important features could be made v bright colours by mapping numbers to colours.
used for remote sensing of data e.g thermal imaging showing heat as colour
nebula images are not colourised. colourised to represent the elements that are known to be present
Manipulating for noise reduction
Noise is unwanted interference, usually appears as bright or dark spots in images.
In the process of sending images some pixel values can be lost
two ways of reducing noise
- Take the median of surrounding pixels
— lose fine detail, requires more processing power, slower but a much better method, better at preserving fine edges
- take the mean of the surrounding pixels called smoothing
- – Spreads damage out, blurring of image, less sharp but preserves fine detail
both of these are done to every pixel in the image not just the noisy pixels
Edge detection
Laplace rule- multiply the pixel value by 4 and subtract the value of the north, south, east and west values
OR
take an average of the neighbouring pixels and subtract it from the centre pixel
where the light intensity changes sharply there is an edge
Analogue and Digital signals
Digital signals are represented by binary numbers, number of values a digital signal can take depend on number of bits.
Analogue signals are not limited in the values they can take, they vary continuously over a range of volume and frequency
Noise effect on different signals
Digital signals are resistant to effects of noise, pick up disturbance from electrical signals
think of the diagram you’ve seen since day 1
Digitising analogue signals
Take the value of the signal at regular time intervals, then find the nearest digital value. Each digital value is represented by a binary number, so you can convert the analogue values to binary numbers.
Will not be exact but close enough
How well a digitised signal depends on what two things?
The difference between the possible digital values (resolution) and the time from one sample to the next.
higher resolution i.e more possible digital values there are, the more closely the digitised signal will match the original
high resolution is needed for CDs / DVDs
low resolution is used for telephone lines (need to be audible but not completely accurate)
Digital advantages/Disadvantages
Advantages Sent received and reproduced more easily can be compressed to reduce size, manipulated easily for artistic effect Represent different types of info can be easily produced from computers
Disadvantages
Digital never reproduce analogue exactly
info can be lost
signals are much more easily intercepted or hacked without owners knowledge or consent
Analogue ad/disad vantages
Advantages
Can not be hacked as easily
wide range of info
Disadvantages
noise is easily picked up
info is lost very easily
The musical note example of signals madeup of lots of different freqs
Waves can contain multiple frequency and they will superimpose over each other
amplitude of final signal is the sum of amplitudes of all other signals in that instant
fundamental frequency is the lowest frequency wave that makes up the sound wave
find the shortest repeating part, calculate the inverse of it’s period
How does noise limit sampling?
If the original signal contains noise, fine resolution will reproduce small vibrations caused by noise
resolution is limited by the ratio of the total variation in the signal to variation caused by noise
number of bits for sampling equation
Maximum number of bits = log base 2 (total variation/noise variation)
b=log2(Vtotal/Vnoise)
minimum sampling range?
Twice the maximum frequency to ensure all with in spectrum are transmitted accurately
music needs high sampling rate to make sure high freq details aren’t lost (44100 Hz)
DVDs (192000 Hz)
Flaw of low sampling rate
Can create low frequency signals called aliases that were not in the original signal at all
Avoiding aliases equation
minimum rate of sampling > 2 x maximum frequency of signal
Rate of transmissions equation
Rate of transmission = samples per second x bits per sample
Bits per sample
High enough that the transmitted signal closely matches the original, but not so high it is affected bu noise.
(size of bits should include freq of noise, check your notes you have really good notes on this yay)
Time taken to transmit signal equation
time taken to transmit a signal = number of bits to transmit/rate of transmission
