Digital New
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Transcript of Digital New
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Digital
CinematographyReturn of the Points
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Reality is out there.
We perceive reality through some mediation. But
our perception is always continous.Anything which is a true or analogous recording of
recording of reality is known as analog.
An image can also be made in a discrete way.
Pointillist painters like Seurat always knew that.
In electronic terms, the presence or absence of a black
dot is known as the absence or presence of a electric
charge at a particular area in the picture frame.
For convenience the absence or presence of the charge
can be referred to as 0 or 1.
In mechanical-electrical devices this means switch-off
or switch-on.
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Information from the real world are carried over to
the human sensory organ through some mode of
communication.
Such communication packages are commonlyknown as signals.
Signals can be continuous like the reality world, or
they can be broken down into pieces for easy
transport and copying (from one system to another.)A signal can be time-varying or
space-varying, depending on what
it is doing.
To remap the signal to a digital
domain, we need to take samples at
discrete points, for a regular time
or space interval.In principle, this is same as
scaling factor for an Atlas. But that
is analog (continuous in nature,
while digital mapping is discrete.
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The big question is how the sampling is done for anyanalog signal, specially the image and video signals.
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Sampling, otherwise known as the first step to translate analog signals to
digital domain, is a process of remapping the continuous signal through timeand/or space to a number of discrete values (the position and orientation of the
signal in the domain through a regular time and/or space interval.)
That can be transcoded as the presence or absence of the signal in the domain
(sometimes known as the matrix) at a particular point. It is always stored as an
electric charge.
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If the signal is not present at a particular point in the matrix, it will bea zero (no charge), while presence will be shown as 1.
The value of a signal at a particular point in the matrix depends on itsposition in the matrix and its direction vectors.
This is very similar to the graphs of the equations we used to drawin school. It follows the same principle.
The truthfulness of the digital signal depends on how frequentlysamples are taken from its analog form.
Normally, an image or video signal can be closely reconstructed inthe digital domain if the sampling rate is higher than twice the highestfrequency in the signal.
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Now what does that mean?
We all know how an aliased image looks.
Anti-aliasing is not really the solution.
Aliasing arises when the signal is discretely
sampled at a rate insufficient to capture the
changes in the signal (change over time or
space.)
The only solution is to reach a minimal
sampling rate.
For most practical purposes, a sampling rate of twice the highest
frequency in the signal is enough (or twice the frequency, if the signal is
uniform throughout as the one below.)
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What happens if we take a sample at a rate lower
than the signal waves highest frequency?
We can see the nature of the wave can partially, or completely, change, if
we do not follow this simple rule of sampling.
The reconstruction of the signal is now false, and the playing back of thissignal as an image or video will definitely present wrong information, in
terms of presence of signal at a point, its value and its direction.
All such wrong information are collectively known as aliasing.
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Even analog has aliasing!
The Wagon-Wheel effect
If the wheel of a cart or car with
spokes rotate at a speed less than
the sampling rate of the reality
(yes! Analog has a sampling rate
too!), the wheel seems to be
rotating backwards on the screen.
For analog film, the samplingfrequency is its frame rate (ie, 24
frames per second.)
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What will you do if your sampling rate is fixed?
One very common approach, which
we just have seen, is known assmoothing, or purposefully blurring
the signal.
Smoothing is also known as anti-
aliasing in computer graphics world.In human eye, the lens can not
discern a spatial variation more than
60 cycles per degree.
According to Nyquist theorem, the
number of photoreceptors per degree
of vision field should be at least 120degree.
Recently neurologists proved that
indeed the number is around 120!
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Blur
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What is the highest frequency?
The highest frequency of any signal is also known as its bandwidth.
For a black and white film it means, how many times the medium can
switch between the building blocks of visual information (ie, the presence of
a black dot on a white screen, or the reverse.)
For analog PAL monochrome TV image, the bandwidth is practically 5.5
MHz.
The modern HDTVs handle 20 MHz or more of bandwidth.
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How is the signal stored in Digital?After sampling, an image can be stored
as a discrete value of either 1 or 0, for a
particular point in the frame, with
another set of 1 and 0 determining the
pixels brightness.
Depending on the bit Depth of the
pixel, as many values can be stored asluma information.
A 1 bit picture can store 21 number of values per pixel.
This means black or white.
A 2 bit picture can store 22 diferent values, translating the
image in black, white and two shades of grey in between.
Accordingly 8 bit corresponds to 256 different greytones.
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If the image is color, instead of monochrome, there are three
separate color information channels.
For each such primary color channel there is a bit-depth
involved, making the number of tonal variations for the
primary color.
If it is a 8-bit color depth for each channel (RGB), there is a
totality of 24 bit-depth involved in the image.
As we know, we can get other colors by mixing these threechannels, in terms of tonal variation.
Peak white can be obtained by mixing all the three channels
in their highest tone (tonal peak.)
Black can be obtained by mixing them in their tonalminimality (that is same as absence of any colour pixel in
that area in the image.)
In between there are 254 shades of grey.
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HHow is the image processed?
After the image is acquired as combination of 1 and 0s. It has to be
handled in a way so that it can talk to the computer interface (ie, the OS
running inside or outside the chip.)
For that purpose, the binary numbers (voltage or lack of voltage) are
coded into something which the machine can read.
A translator program helps the machine on this job. That program is
called a codec.
At the time of getting back the voltage information as pixel information
on the TV, the reverse translation process is on the run.
This whole translation process is known as compression (compressing
the information is just one part of the process actually.)
There are lossy and lossless image and video compression methods.
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Compression came to rule the as the digital avatar of theanalog signals were too heavy for the channels available.
It was not technically possible to mass produce VCRs or
Camcorders that operate at 216 Mbps, in the 1980s.
With the new HDTV systems at the end of 1990s and in the new
Millennium, the bitrate increased manifold. So compression
persisted.
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Digital Compression takes place by rejecting information
(a) that could be easily reconstructed
(b) that is considered nonessential
the absence of which is not noticeable
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Seen as such, even analog TV worked on the principle of
compression.
The interlace principle in itself represents a 2:1 compression.
A progressive scanning requires a bandwidth twice as large.
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As mentioned already, there
are two otypes of
Compressions
Lossless
Lossy
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Every signal has two parts
(a) Entropy : An unpredictable part which can not be erased orcompressed
(b) Redundancy : A part that has a very high degree of repetitiveness,
highly predictable, and can be easily reconstructed from a simple initial
indication
All compression methods function by rejecting as much redundancy as
possible while preserving the entropy untouched.
Practical compressors retains some residual redundancy, but ensuringthat no entropy is lost.
If entropy is lost, video signal becomes choppy (eg, image telephony)
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Three Types of Video Redundancy
Spatial Redundancy: Spatial
Compression also known asIntraframe
Compression. The totality of the
removable redundancy is located inside
one single frame.
Temporal Redundancy : Temporal
Compression also known asInterframe
Compression. An extreme example is
freeze frames.
Statistical Redundancy: Elements that
are regularly repeated, including the
vertical and horizontal sync pulses.