Imaging
Toolkit - Concepts
Alpha Channel
Most 32-bit graphics have 4 channels. The first 3
channels are the Red, Green and Blue Channels with 8
bits each. These channels carry the actual image
information. The 4th 8-bit channel or the alpha channel
is really a mask. It specifies how the image's pixel
colors should be merged with the background pixels when
the image is displayed on top of the background.
As such, alpha is commonly used to refer to the opacity
of a pixel. The alpha channel extends the basic 1-bit
transparency mask by allowing 8-bits or 256 levels of
opacity.
|
Annotations
Annotations can be considered as additional non-image
add-on data that is to be displayed together with the
image data. For example, a user may wish to highlight an
area of the image but does not wish for the highlight to
be permanently part of the image. The highlight is
implemented as an annotation and can be stored either
within the image file or as an external annotation file.
However, not all image formats support storing the
annotations separate from the image data but within the
same image file.
|
|
|
|
Original image of
a document
without annotations |
A highlight
annotation (in yellow)
applied to the image |
There are many types of annotations - highlights,
stamps, text, lines, etc. However, there is no standard
that is adhered to by the different imaging toolkit
providers.
|
|
Anti-Alias
Anti-aliasing is the process of remove the jagged edges
from the lines in an image. For example, drawing a
diagonal line on a low-resolution raster display yields
an undesirable "staircase" look. Anti-aliasing
smoothens out the jagged edges of an image by padding
pixels with intermediate colors. If black lines are
drawn on a white background, anti-aliasing pads with
surrounding pixels of shades of gray. If red lines are
drawn, anti-aliasing is performed using pixels of shades
of pink.
|
|
|
|
|
Jagged edges of the
diagonal
line |
Anti-alias applied |
Notice that the jagged edges of the diagonal line
are smoothened out when anti-alias is applied. To
illustrate how this effect is produced, the image
is zoomed in to allow the padding to be seen.
|
|
|
|
Zoomed image of
the
diagonal line |
Zoomed image when
anti-alias is applied |
|
|
Dithering
Dithering is a process of overcoming physical color
display limitations at the device pixel level by
integrating the display output several neighboring
pixels. Although a display device (especially the older
ones) may only be physically able to display a limited
number of colors, if the person viewing the display is
sufficiently distant from the display, dithering can be
performed to achieve an apparent improvement in the
perceived number of colors.
For example, human vision has poor acuity for blue
spatial detail but good color discrimination capability
in blue. As such, dithering blue across two-by-two pixel
arrays can produce four times the number of blue levels
without perceptible penalty.
Effects
Effects are transform functions that are applied for
artistic purposes. For example, the Posterize effect
decreases the number of colors or gray-scales in an
image to create a poster-like image. Another example is
the Perspective effect that makes distant objects appear
smaller than the objects of focus. The perspective
effect also makes parallel lines appear to converge as
the lines approach the horizon.
Filters
Filters are transform functions that remove a selected
image data from an image based on a formula. For
example, the Median filter is a spatial filter that is
based on an input pixel and its 8 neighbors. The
resulting value is the statistical median value of the 9
pixels in sort order. A median filter is normally used
to reduce speckling noise from a gray-scale image. A
major strength of the median filter is that it preserves
edges better.
Gamma Correction
Monitors and cameras are inherently non-linear devices.
For example, the intensity of the luminescent phosphor
on the monitor display is non-linear. This means that a
pixel of intensity 128 does not appear twice as bright
as a pixel of intensity 64.
Gamma correction is a non-linear function that is used
to correct for these non-linear display aspects. Gamma
correction controls the overall brightness of an image
and the ratios of the colors of red to green to blue.
Images with the wrong gamma correction will either
appear too bright or too dark.
Layers
Layering is a method used to produce a composite image
from individual layers. Each layer can be considered as
a transparent sheet which can contain image data,
effects and filters; drawn on; or have elements added to
it. These layer are then arranged and stacked on top of
each other transparently to produce a final image.
On of the major benefits of having layers is that each
layer can be processed independently of the others. Any
editing, enhancements, resizing or repositioning of a
single layer will not impact other parts of the
composite image.
Most imaging toolkits support some kind of layering as a
standard feature.
Raster versus Vector Methods
A raster image is an image that is defined by rows of
pixels. Each pixel of the image is specifically defined.
An example of a raster image is a bitmap. An image is a bitmap if it contains a value for each of its pixels.
A bitmap is a map consisting of rows and columns of
pixels. The value of each pixel is stored in one or more bits of data. For black and white images,
1 bit is sufficient to represent each pixel. For colors and
grayscale, more than 1 bit is required to represent each
pixel - e.g. 8 bits or 24 bits for each pixel.
The raster method of representing images is very much
opposed to vector method in which images are defined
using a series of polygon nodes joined by lines. Each
image is self-contained with properties such as color, shape, outline, size, and position on the screen.
As such, vector images can have its properties changed
multiple time while retaining the original clarity and crispness of the image.
Also, vector-based images are resolution independent and
the images appear at the maximum resolution of the output
device - e.g. printer or monitor.
|
Transparency
Transparency is an attribute that is designated to
certain areas or pixels of an image to specify that that
area or pixel has no color information. As such, when
the image is displayed, the container displaying the
image displays does not display any image information in
the transparent area but instead displays the background
color. Transparency is typically implemented by using a
simple 1-bit (Transparent/Not Transparent) mask to
specify whether an area or a pixel is transparent.
|
|
|
|
A non-transparent
white-background
image containing the letter A
placed on a blue background |
The white
background of the image
is defined as transparent and then
placed on a blue background |
Transparency is especially useful as it allows the
creation of rectangular objects that appear as if they
are irregular in shape. This is achieved by defining the
border rectangular edges as transparent so that the
background shows through. Not all image formats support
transparency. |
|
|
|
 |
|
