pixel
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PixelPixel- Is short for Picture Element.
The amount of pixels in an image depends on the resolutions of the image, the more pixels in an image, the higher the resolution. The less
pixels in an image the lower the resolution.
Pixel intensity means that the intensity of each pixel is variable. In colour image systems, a
colour is typically represented by three or four component intensities such as red, green, and
blue, or cyan, magenta, yellow, and black.
Pixel
The image on the right is an original image from the internet with a resolution size of 1920x1200. The image on the left is a zoomed in version
of the original image on the right. The zoomed in version shows all the various pixels which are use to make up that part of the image.
Raster Image
s
A raster image, also called a bitmap, is a way to represent digital images. The raster image takes a
wide variety of formats, including .gif, .jpg and .bmp. A raster image represents an image in a series of bits of information which translates into pixels of the screen. These pixels form points of colour which create an overall finished image.
When a raster image is created, the image on the screen is converted into pixels. Each pixel is
assigned a specific value which determines its colour. The raster image system uses the red,
green, blue or (RGB) colour system.
Raster images are compressed into lossy or lossless compression and these can be used for various
reasons. For lossy compressions it should be used If the raster images are only background images, for faster data loading and retrieval and if less storage space is needed. While on the other hand lossless compression should be used f the raster datasets
are to be used for deriving new data or visual analysis, if using discrete data, if you don't plan to
retain the original data and f your inputs are already lossy compressed
Raster Image Files
.bmpBitmap Image File
.gifGraphical Interchange Format File
.jpgJPEG Image File
.pngPortable Network Graphic
.psdAdobe Photoshop Document
.pspimagePaintShop Pro Image
.thmThumbnail Image File
.tifTagged Image File
.yuvYUV Encoded Image File
Vector Images
Vector images are actually stored as mathematical rules - widths, heights, curves, proportions, ratios. Where raster images have a set height and width and look pixelated when stretched beyond these boundaries,
vector images render themselves to the space given to them, such that they are resolution independent. This
means you can increase and decrease the size of vector images to any degree and your lines will remain crisp
and sharp, both on screen and in print.
Vector images have a number of formats, which exist for storing vector images, each with their advantages. It is important to note that, by their very definition, vector
images are small in comparison to raster images when it comes to file size.
Another advantage of vector images is that they're not restricted to a rectangular shape like bitmaps. Vector
objects can be placed over other objects, and the object below will show through.
Most examples of vector images are used for logos such as the examples (shown on the left), but there are
other uses such as for vector art (shown at bottom left of the screen).
Vector Image Files.ai Adobe Illustrator File
.drw Drawing File
.epsEncapsulated PostScript File
.ps PostScript File
.svgScalable Vector Graphics File
This is sometimes called ‘Pixel Depth’ or ‘Colour Depth’. Bit depth is how many unique colours are available in an image’s colour pallet in terms of the number of
0’s and 1’s, or ‘bits’, which are used to specify each colour. This does not necessarily mean that the image uses all these colours, but that it can instead
specify colours with that level of precision. The greater the ‘bit depth’ the finer the levels of change that can be recorded so the higher fidelity the gradations of the
image.
Bit Depth
Bit’s Per Pixel (BPP)Bits per pixel or (BPP) is the number of bits of information stored per pixel of an
image or displayed by a graphics adapter. The more bits there are in the image, the more colours that can be represented within the image, but the more memory is
required to store or display the image.
Bits Per Pixel Number of Colours Available Common Name(s)
1 2 Monochrome
2 4 CGA
4 16 EGA
8 256 VGA
16 65536 XGA, High Color
24 16777216 SVGA, True Color
32 16777216 + Transparency
48 281 Trillion
Monochrome 256Monochrome describes paintings, drawings and photographs in one colour or in shades of one colour. A monochromatic object or image has colours in shades of limited colours or hues. Also monochrome 256 is kind of like grey scale accept monochrome has 256 different shades of grey, black and white.
True colour is a method of representing and storing graphical image information in an RGB colour space which a very large number of
colours, shades, and hues can be displayed in an image, such as in high quality photographic images or complex graphics. Usually, true colour
is defined to mean at least 256 shades of red, green, and blue, for a total of at least 16,777,216 colour variations, which can be used in
various images and videos.
High Colour and True Colour
High colour graphics is a method of storing image information in a computer's memory and that each pixel is represented by two
bytes. Usually the colour is represented by all 16 bits, but some devices also support 15-bit high colour.
Greyscale and RGBA greyscale digital image is an image in which the value of each pixel is a
single sample, in which it carries only intensity information. Images of this sort, also known as black-and-white, are composed in various shades of
grey, varying from black which is the weakest intensity to white which is the
strongest intensity. Also grayscale images have many shades of grey in
between.
The RGB colour model is an addictive colour model in which red, green and
blue colours are added together in various waves to reproduce a variety of
different colours. RGB is used on a variety of things such as in images and
photographs, on televisions, on cameras, and RGB is what helps create all the various different colours which
we see on images and on television etc.
YUV - Luminance and Chrominance
YUV is a colour space typically used as part of a colour image pipeline. The Y component determines the brightness of the
colour, the U and V components determines the actual colour itself. Y ranges from 0 to 1 (or 0 to 255 in digital formats), and U
and V range from -0.5 to 0.5 (or -128 to 127 in signed digital form, or 0 to 255 in unsigned form).
Y' value of 0 Y' value of 0.5 Y' value of 1
HSV – Hue, Saturation and Value
HSV (hue, saturation and value) defines a type of colour space. It is similar to the modern RGB model. The HSV colour space has three components: hue, saturation and value. ‘Value’ is sometimes substituted with ‘brightness’ and then is can be known as HSB.
Saturation - indicates the range of grey in the colour space. It ranges from 0 to 100%. Sometimes the value is calculated from 0 to 1. When the value is ’0,’ the colour is grey and when the value is ’1,’ the colour is a primary colour.Value - is the brightness of the colour and varies with colour saturation. It ranges from 0 to 100%. When the value is ’0′ the colour space will be totally black. With the increase in the value, the colour space brightness up and shows various colours.
Hue - represents colour. In this model, hue is an angle from 0 degrees to 360 degrees.
Angle Color
0-60 Red
60-120 Yellow
120-180 Green
180-240 Cyan
240-300 Blue
300-360 Magenta
Image CaptureImage capture is when an image is captured or stored. Many items can do this such as:
• Digital cameras – a camera that takes video or still photographs, or both, digitally by recording images via an electronic image sensor, you can then able to upload the image/video onto a computer by a small memory card.
• Camcorders - electronic device that combines a video camera and a video recorder into one unit, you are able to record videos and then can upload the video onto a computer via a memory card.
• Scanners - a device that optically scans images, printed text, handwriting, or an object, and converts it to a digital image.
Image CaptureDifferent models of cameras and camcorders have different resolutions, some are high resolution and some are low resolution. This is because it depends on the amount of pixel’s per inch in each image or
video from the camera or camcorder. The higher the amount of pixels in each inch of the image or video the higher the resolution which means the image or
video comes out in good quality, but if there is a lower amount of pixels in each inch of an image or video then it is of lower resolution. Which means that the image or video comes out in bad quality.
There are many different memory cards for camcorders and cameras which have different
memory size’s such as 2gb,4gb,8gb 16 gb and these different sized memory cards can hold different amounts of images/videos. Also different images
with high or low resolutions take up different amounts of memory, for example high resolution images take up more memory than low resolution
ones.
Image OptimizationThis was done on Adobe
Fireworks. To start off with I found an image of the internet and copy and
pasted it onto the piece of software but I wanted to make sure that the image was of a high resolution so
it was clear.
After this I clicked on ‘File’ (top left hand corner of the screen) and then scrolled
down the menu until I reached ‘Image Preview’, which I then clicked on
which then brought up a new window also showing
the image.
This is the screen that came up after I click on ‘Image Preview’. On this you can do a variety of things
to the image to change its properties and also you are shown information about the image such
as – it would take 9 seconds to upload this image if I wanted it on
the internet. Also on ‘Image Preview’ I can change various things on the image such as its resolution, size and even its bit
depth. One thing which can be changed is the
amount of pixels which are on the image, this means I can change the memory size
of the image but also it means I can change the resolution of the image as well, (increasing pixel count – higher resolution, decreasing pixel count –
lower resolution). This means if I decreased the size of the image, it would
reduce the memory size and it would also make the image quicker to upload if I wanted to upload it onto the internet.