Hi and welcome to this second video
about binary coding.
We saw previously
how to represent information in the form of bits
We are now going to focus more precisely
on the method to use this technique
to store images and sounds.
Nowadays, images are extremely used
for video games, television, virtual reality.
How do we actually display them?
We will use what we call pixels.
Pixels are composed of small dots
of different colors, green, blue and red,
that we will turn on to give the eye
the illusion that this is a particular color
because they are so small that the eye
can't distinguish the three components,
red, green and blue.
So the eye will believe there is only one color.
These pixels will be used for display
but also for a lot of things
including manipulation as the information
in the computer will be stored the same way,
whether it is for display,
manipulation, printing, etc.,
we will use this technique using dots
called pixels to represent images.
To code pixels, we will use sequences of bits.
Each of the image's pixels, each of the image's dots
will be represented by a set of bits.
It will depend on the quantity of colors
we would like to display.
If we have a black or a white image,
each pixel will have only one bit
that says "Is it white" or "Is is black".
If we want an image in grayscale,
we will be able to use 8 bits
for each pixel, for example.
8 bits which gives us
256 possible values, 2 power 8.
0 will be black,
255 - the maximum - will be white,
and the intermediate values will be gray,
more or less dark.
And we can generate colors
by combining red, green and blue as we said.
Here we will use 8 bits for each component.
8 bits for red, so if there is 0 for red,
there will be no red in the color.
If we have 255 for red,
the color will be more red.
Each component will have a value
between 0 and 255
and by combining them, we can chose the color
among lots of different colors: 16 million.
The next question is "If I have a sequence
of bits that corresponds to an image,
how do we know if 24 bits
corresponds to 24 black and white pixels,
because each pixel uses one bit
or has one pixel in colors,
because each of these pixels uses 24 bits".
We will have to add information
to specify that my image is stored by pixels
and each pixel is coded with a certain number
of bits, black and white, gray or color.
And we will also need to specify the image size.
Is it kind of rectangular? Elongated?
Vertical? Is it a square?
The image will be a set of pixels
defined by a set of bits,
but will also be defined by general
characteristics: size, dimensions, height, width
and also the number of bits used for each pixel.
What we have just described
are images called bitmap,
which is a set of bits
that will describe every pixel.
In practice, the computer
doesn't know the content of this image.
On the right side of this presentation here,
we can see a disc
which is represented by pixels.
The computer doesn't know this is a disc.
If it wants to know it, it will need
an algorithm for pattern recognition.
If it doesn't have it,
it only knows there is a set of pixels
with more or less black colors and that's it.
In practice, an image like this disc,
we could code it in a more practical way.
Here, for example,
instead of saying this is a set of white pixels
if we are not in the disc,
black if we are in the disc
and a little bit gray on the edge of the disc,
we could directly say the disc is black,
of such size
and in a particular area in the image.
It would be more specific
as we would not have problems
at the edge with the slightly gray dots
because they overlap on the edge of the disc,
and it would be more succinct.
Instead of describing every pixel,
we would only describe the disc,
its color, size, position and that's it.
This is what we call a vector image.
Rather than describing each pixel of an image,
we will describe how to build
the image with mathematical forms.
Mathematical forms can be discs, rectangles,
polygons,
more complicated mathematical curves.
We will give a set of characteristics
to describe this mathematical curve
and also information
regarding the way to color it,
how to eventually color the inside
with gradations for example,
but always in the mathematical form,
with numbers.
So this is good for technical drawings,
as, in general, technical drawings
represent very precise forms,
squares, rectangles,
circles with specific colors.
However, it is more complicated for pictures
as pictures have generally
a lot of different colors
with shapes that are not necessarily
mathematical forms
as we are used to describing them
with squares and rectangles.
So it may not be adapted.
For pictures, it will be bitmap images
with pixels like we have seen before.
We will now look into sound coding.
Sound is sound waves coming in our ears
which are, at every moment, a height
and a volume representing the noise that we hear.
In practice, we have an infinity
of values for every successive time.
We can't code them all because we would have
an infinity of data to store in the computer.
What we will do is what we call sampling.
Sampling consists
in dividing time in small periods
and in saying for example
"During the millisecond that just passed,
volume and height
of the played note was this one".
We will average, approximate
during small periods of time
in order to avoid to store too many values.
We will need, of course,
to do that in an adapted way.
The human ear shouldn't tell the difference,
so we will have to use
a sampling frequency which is high enough
so that the human ear
can't tell the difference between
having averaged
on a millisecond and the real signal.
And we shouldn't do too much sampling,
and have a too high frequency
as we would have too much data to store.
So we will do sampling with something which
corresponds to what the human ear is capable,
which is to hear frequencies
between 20 hertz and 20 kilohertz.
We will have a set of successive values
for each of these small periods of sampling.
For each of these values,
we will have a set of bits that will describe
what the height, volume, etc. of the note is.
So this sequence of bits
will represent the sound.
As for the images, we will see a header which will
specify what the frequency of the sampling is.
To make it clear, I will give you a number of values
and each values corresponds
to one millisecond of the sound, for example.
That was the usual sound coding.
As for images where we could create
bitmap images by pixels
or vector images with mathematical formula,
it is also possible to make
something different for the sound.
With a musical piece, sound will corresponds
to a music score played by instruments.
What is a music score?
It's successive notes caracterised
by height and length of time.
The instruments that will play them
have also characteristics that we can describe
such as the type, the timbre, etc.
We can recreate the piece of music
by using the information on the score
and on the instruments that play it.
This will be like for a vector image,
we describe the image by the way
we create it, using mathematical forms,
so here we will describe music
explaining how we created it
from the music score and the instrument.
This enables to code sound in a different way,
it is not necessarily adapted for each case,
but it can be an interesting
approach for pieces of mucic,
complementary to the approach
we saw earlier.
What should we remember from this chapter?
First of all, we can code images
and sounds with sequences of number of bits,
like we did earlier
for numbers or letters of a text.
Then, we will also have computer programs
that will interpret this coding,
meaning reading the image information,
what is the height, size,
number of bits used for the pixels,
which will enable the computer
to display this image on the screen,
to print it, to manipulate it, etc.
Similarly, the computer will have a program
to read sound information, to play them on a speaker.
On the contrary, to bring
an image or sound to the computer,
a program will receive the signal
and translate it in coding
with the exact opposite strategy.
Between the two, the data is coded
with the bits we saw earlier.
And whether it is to store
on the hard drive, in memory,
a transfer on the internet between
two computers, audio or photo manipulation,
the data will remain coded.
It's only when the data will enter
the computer to record
or to be read or displayed by the computer
that we will decode them
to give them to human beings.