Imaging and Signalling Flashcards
Refraction
Occurs at a boundary when a wave changes speed. Bent towards/away from the normal. If light is slowing down (less optically dense to more optically dense), bends towards normal
Optical density
The more optically dense a material is, the slower light will travel in it
Absolute refractive index=
c/v (where c speed of light in a vacuum, and v is speed of light in the material)
What do lenses do?
Change the curvature of wavefronts by refraction.
Uncurved waves through a lens
If waves are uncurved when passing through a lens, and pass through at 90deg to the lens (parallel to the lens axis), they will be given spherical curvature, centred on the focal point of the lens
Focal length
Distance between lens axis and focal point.
Power of a lens=
1/f (f is the focal length. Power measured in dioptres, D. According to equation, more powerful - thicker - lenses have a shorter focal length, as they curve the wavefront more)
Power of a lens
How much curvature a lens adds to a wave passing through it
Curvature of a wave=
1/radius of curvature
Lens equation:
1/v = 1/u + 1/f (where v is the image distance, u is the object distance and f is the focal length)
What must you remember when using the lens equation?
Measure distances to the left of the lens axis as negative, and the distances to the right of the lens axis as positive - cartesian convention. Always measure distances from the lens axis
Linear magnification=
size of image/size of object = v/u
Wave equation:
v=f(lamda). Derived from v=d/t, where d is (lamda) and t is 1/f (speed is velocity)
Transverse waves
Medium oscillates at right angles to the direction of travel. E.g. EM waves
Longitudinal waves
Medium oscillates parallel to the direction of travel. E.g. sound waves
Bit
A single binary digit
Byte
8 binay digits - 8 bits
Number of alternatives=
2^number of bits (N=2^I)
Number of bits=
log(2)(number of alternatives) (I=log(2)(N)
Pixels
Pixels are a string of binary numbers, coding for a specific colour/shade. Depending on how many bits there are in each pixel, there will be a varying number of shades/colours in the image
Brightening an image
Adding a fixed positive value will brighten the pixels
Improving contrast
Multiplying by a fixed positive value that is greater than 1 will improve the contrast
Smoothing edges
Replace each pixel with the mean of its values and that of its neighbours
Removing noise
Replace each pixel with the median of its value and those of its neighbours
Finding edges
Multiply a pixel by 4, then subtract the N,S,E and W (directly above/below/to either side) neighbours - the Laplace rule
False colour
Changing what a pixel codes for - e.g. a value of 2 may have been a dark grey, but could now be a deep orange. Can highlight important features in bright colours this way.
Digital signals
Represented by binary numbers. Number of levels depends on number of bits. Limited in the values they can take
Analogue signals
Vary continuously
Advantages of digital
Sent, received and reproduced more easily than analogue (limited number of values)
Resistant to effects of noise
Can represent images and sound in the same way - a string of bits
Easy to process using computers (computers are digital devices too)
Digitising analogue signals
Sample the signal at regular time intervals, and find the nearest digital value - round to the nearest level.
Resolution of a digital signal
Determined by the number of bits. The difference between the possible digital values. How close he analogue signal is to the digital signal - how much the level changes
Disadvantages of a high resolution
If resolution is too high, then noise in the signal will be picked up, which is not useful
Maximum number of bits=
log(2)(Total variation/Noise variation) (b=log(2)(Vtotal/Vnoise))
Sampling rate
If you sample too infrequently, details of high frequency will be lost. Low sampling rates create aliases - frequencies that weren’t in the original signal
Minimum sampling rate=
2 x maximum frequency of signal
Disadvantage of digital
Can’t reproduce analogue signals exactly, some information will be lost
Spectrum
The frequencies that make up a signal. Spectra graphs are line charts (bars that are lines), with the height of the voltage
Analogue bandwidth
Range of frequencies within the signal. Highest frequency - lowest frequency
Carrier waves
How communication signals are transmitted. Have to separate actual signal from carrier signal to receive information
Limits of bandwidth
If there is only a limited amount of frequencies to transmit on (which there is), the bandwidth of each frequency limits how many channels can be transmitted. Signals can’t overlap.
Rate of transmission=
samples per second x bits per sample (rate in bits s^-1)
Polarised wave
Only oscillates in one direction (perpendicular to plane on travel)
Polarising a wave
Passing a wave through a filter will polarise it. Only transverse waves can be polarised. 2 polarising filters at right angles will completely block a wave, as all directions of vibration will be blocked. Reflecting a wave/passing it through cloudy water will polarise it (can’t oscillate in direction of travel).
Uses of polarised light
Radio and TV signals are polarised
Communications satellites use different polarisations for signals of same frequency bandwidth, reducing interference
Bees use polarised light to navigate
CD players use polarising crystals
Polaroid filters
A line of horizontal rods will absorb horizontally polarised waves, as the wave will cause electrons in the rods to oscillate. However, vertically polarised light can pass through.
Information in an image=
number of pixels x bits per pixel
Digital bandwidth
1/2 rate of transmission or rate of transmission
