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Unit 11 - Digital Graphics and Animation
11.1 How digital graphics and animation are used in computing
Task A – 11.1
P1: Explain the characteristics of digital graphics and animation
Digital Images:
All images displayed by a computer are known as “digital images”. However, there are
several ways these images are created.
There are currently two types of graphics to create and store digital Images.
The two types of graphics are raster graphics and vector graphics/images.
Raster Images
Raster graphics are graphics which “render images as a collection of countless tiny squares
or grids”.Together, these countless number of squares form a map of tiny squares,
equivalent to a dot in front of the human eye, which are professionally called bits to form a
bit map.
A bit is the smallest unit of storage in computing and it can store data only in the form of 1
and 0s. The simplest image is that of 1 bit which only contains two colours, black and white.
As the bits increases so does the options of colours and the data itself, resulting in a higher
quality image.
In reference to Digital Graphics and Animation, a bit is mostly used to contain a specific
colour and shade to it. This is also known as Bit Depth (bits per pixel); the information which
encodes a colour in an image. The higher the bit depth of an image, the more colours it can
store. The simplest of images are 1-bit images, and can only contain black and white as
mentioned above. An 8-bit image can store, 256 colours, 24 bits can contain over 16 million
colours and so on. However, this comes at a small price. As the bit depth of an image
increases so does the file sizes, and drastically, as more colour information has to be stored
for each pixel in the image.
Bit depth is also responsible for the resolution of an image. The greater the number of pixels
in an image, the higher the resolution of the image, and thus the higher the quality of the
image. Again, this requires more backed storage to save it. One drawback is though
however, that the resolution of a raster image depends upon device, or rather the dpi (dots
per inch) of a device, making it device dependent. For example, A PS5 which is able to run
on 120hz with 4k resolution, would not work to its maximum capability on a 1080p 60hz
monitor.
,1
Whilst this all sounds ever-evolving, the only flaw is that higher quality images take up way
too much space. Fortunately, there is some tweaking to this too, and that is that there is
compression. Popular compression types are PNG, JPEG, and GIF etc.
Even though all of these compress a file down, they have major differences to them. For
example:
PNG: It is a lossless compression type, which means that when the file is being compressed
down, the whole file is being shrinked down so the data is not being lost. Another key
feature it has it that it supports transparency, so it is widely used for logos and icons, to
enable sharp contrast of colours, bring transparency and also keep them of high quality.
JPEG: This compression is a lossy compression. It works by removing data/redundancies in
an image and as a result bringing the size of the file significantly down. Best for
photographers, as it compresses the size of the files down a lot, but still displays the image
very vibrantly as the data lost in terms of the actual file size is minuscule. Also, the
compression is irreversible and once the data is lost it is not recoverable.
GIF: Old style technique, which is not used as much currently, but mostly for some simple
animations. It works by capping the bit depth of an image to a maximum of 8 bits.
2D Arrays
The pixels stored in a raster image are organised using a 2D array. A 2-dimensional array is
essentially a grid. It is just a set of data which is organised using rows and columns – just like
x and y coordinates.
Dimensions
All the data (no matter if it’s text, digits or even an image) it is stored in a stream of binaries
(0s and 1s). For this stream of data to make sense to the computer (and to access it more
efficiently) it has to be stored and organised in distinct dimensions of the array.
This data which is stored in arrays is known as metadata. In the case of an image, it’s
information like the format, the size, etc is stored. The dimensions of an image are “how
many pixels wide and how many pixels tall the image is”. As without this the image wouldn’t
be displayed rightly, (for example, the rows of the wrong length would appear so the
alignment wouldn’t be correct).
Colour Modes
It’s surprising to know how many colour modes there are and they are needed to correctly
decode the information and display it. Some common colour modes are listed below:
Monochrome: In this mode only two colours are available. Each pixel must be of one
of these two colours. Often this is white and black.
Grayscale: In this mode, a range of GREY shades are available. Each pixel must be
one of these shades.
Indexed Colour: This is a multi-purpose mode. It is often known as a compression
technique. In this mode, each pixel of an image is scanned and builds an index of 256
, 1
of the most common colours. Each pixel is then scanned again, and if any colour of a
pixel is different from the ones in the index, they get converted to the ones similar to
the ones in the index. Also since many colours are replaced with a single colour, this
drastically reduces the file size. (It is also possible to create an indexed colour image
with less than 256 colours, even as low as 16. Any power of 2 can be used).
The infamous RGB: Each pixel is made up of three colours – Red, Green, and Blue
that can make up a huge range of colours – up to 16.7 million different shades of
colours! As usually in this mode each pixel is 8 bits per colour, so this makes up 24
bits altogether or 3 bytes per pixel. This means a maximum of 256*256*256 different
colours can be represented, equalling to 16.7 million shades.
ARGB: This is the same as RGB but the main difference between them is that an 8-bit
alpha channel is encoded within. This enables each pixel to acquire any one the 256
levels of transparency, however not all file formats support this at the moment. An
example can be of PNG that supports this. Transparency lets a user to cleanly overlay
images.
Sampling
“It is a method which allows the edges and details of the images to be smoothed out when
resizing or converting from Vectors to Raster graphics”. It works by taking a sample of the
pixels around the edges of an image and the colours, and then it blends the appearance and
makes the rough and uneven edges look smooth.
Unit 11 - Digital Graphics and Animation
11.1 How digital graphics and animation are used in computing
Task A – 11.1
P1: Explain the characteristics of digital graphics and animation
Digital Images:
All images displayed by a computer are known as “digital images”. However, there are
several ways these images are created.
There are currently two types of graphics to create and store digital Images.
The two types of graphics are raster graphics and vector graphics/images.
Raster Images
Raster graphics are graphics which “render images as a collection of countless tiny squares
or grids”.Together, these countless number of squares form a map of tiny squares,
equivalent to a dot in front of the human eye, which are professionally called bits to form a
bit map.
A bit is the smallest unit of storage in computing and it can store data only in the form of 1
and 0s. The simplest image is that of 1 bit which only contains two colours, black and white.
As the bits increases so does the options of colours and the data itself, resulting in a higher
quality image.
In reference to Digital Graphics and Animation, a bit is mostly used to contain a specific
colour and shade to it. This is also known as Bit Depth (bits per pixel); the information which
encodes a colour in an image. The higher the bit depth of an image, the more colours it can
store. The simplest of images are 1-bit images, and can only contain black and white as
mentioned above. An 8-bit image can store, 256 colours, 24 bits can contain over 16 million
colours and so on. However, this comes at a small price. As the bit depth of an image
increases so does the file sizes, and drastically, as more colour information has to be stored
for each pixel in the image.
Bit depth is also responsible for the resolution of an image. The greater the number of pixels
in an image, the higher the resolution of the image, and thus the higher the quality of the
image. Again, this requires more backed storage to save it. One drawback is though
however, that the resolution of a raster image depends upon device, or rather the dpi (dots
per inch) of a device, making it device dependent. For example, A PS5 which is able to run
on 120hz with 4k resolution, would not work to its maximum capability on a 1080p 60hz
monitor.
,1
Whilst this all sounds ever-evolving, the only flaw is that higher quality images take up way
too much space. Fortunately, there is some tweaking to this too, and that is that there is
compression. Popular compression types are PNG, JPEG, and GIF etc.
Even though all of these compress a file down, they have major differences to them. For
example:
PNG: It is a lossless compression type, which means that when the file is being compressed
down, the whole file is being shrinked down so the data is not being lost. Another key
feature it has it that it supports transparency, so it is widely used for logos and icons, to
enable sharp contrast of colours, bring transparency and also keep them of high quality.
JPEG: This compression is a lossy compression. It works by removing data/redundancies in
an image and as a result bringing the size of the file significantly down. Best for
photographers, as it compresses the size of the files down a lot, but still displays the image
very vibrantly as the data lost in terms of the actual file size is minuscule. Also, the
compression is irreversible and once the data is lost it is not recoverable.
GIF: Old style technique, which is not used as much currently, but mostly for some simple
animations. It works by capping the bit depth of an image to a maximum of 8 bits.
2D Arrays
The pixels stored in a raster image are organised using a 2D array. A 2-dimensional array is
essentially a grid. It is just a set of data which is organised using rows and columns – just like
x and y coordinates.
Dimensions
All the data (no matter if it’s text, digits or even an image) it is stored in a stream of binaries
(0s and 1s). For this stream of data to make sense to the computer (and to access it more
efficiently) it has to be stored and organised in distinct dimensions of the array.
This data which is stored in arrays is known as metadata. In the case of an image, it’s
information like the format, the size, etc is stored. The dimensions of an image are “how
many pixels wide and how many pixels tall the image is”. As without this the image wouldn’t
be displayed rightly, (for example, the rows of the wrong length would appear so the
alignment wouldn’t be correct).
Colour Modes
It’s surprising to know how many colour modes there are and they are needed to correctly
decode the information and display it. Some common colour modes are listed below:
Monochrome: In this mode only two colours are available. Each pixel must be of one
of these two colours. Often this is white and black.
Grayscale: In this mode, a range of GREY shades are available. Each pixel must be
one of these shades.
Indexed Colour: This is a multi-purpose mode. It is often known as a compression
technique. In this mode, each pixel of an image is scanned and builds an index of 256
, 1
of the most common colours. Each pixel is then scanned again, and if any colour of a
pixel is different from the ones in the index, they get converted to the ones similar to
the ones in the index. Also since many colours are replaced with a single colour, this
drastically reduces the file size. (It is also possible to create an indexed colour image
with less than 256 colours, even as low as 16. Any power of 2 can be used).
The infamous RGB: Each pixel is made up of three colours – Red, Green, and Blue
that can make up a huge range of colours – up to 16.7 million different shades of
colours! As usually in this mode each pixel is 8 bits per colour, so this makes up 24
bits altogether or 3 bytes per pixel. This means a maximum of 256*256*256 different
colours can be represented, equalling to 16.7 million shades.
ARGB: This is the same as RGB but the main difference between them is that an 8-bit
alpha channel is encoded within. This enables each pixel to acquire any one the 256
levels of transparency, however not all file formats support this at the moment. An
example can be of PNG that supports this. Transparency lets a user to cleanly overlay
images.
Sampling
“It is a method which allows the edges and details of the images to be smoothed out when
resizing or converting from Vectors to Raster graphics”. It works by taking a sample of the
pixels around the edges of an image and the colours, and then it blends the appearance and
makes the rough and uneven edges look smooth.
