Digital Images
The digital representation of visual information.
Image Creation
The method in which visual information is captured and converted into digital images can
be broken down into three categories.
•Human-generated images – images created using some form of
digital painting package
•Computer generated Images – images rendered with a 2D or 3D
software package
•Scanned Images – images created by digitizing live action footage
Pixels & Scanlines
Digital images are made up of an array of picture elements called pixels. Each
picture element contains color information that is broken up into three components
usually red, green, and blue. Using a combination of red, green and blue at different
intensities can represent all colors in the visible spectrum. Images are organized into
strips of pixels called scanlines. All of the scanlines are stacked on top of one
another to produce the final image. Scanlines are a term used to describe image data,
and do not necessarily represent how the image data is stored.
Color
In traditional art classes, students are taught about primary colors (red, yellow, and
blue) and how to mix them to produce secondary colors (purple, orange, and
green). These are primary colors when mixing paint pigments. Color in digital
images is defined by the way colored light combines to produce color. When
painting color is added on top of white to produce color. Digital images must add
colored light to black in order to produce color.
RGB
Red Green Blue
The RGB Color Space is considered and additive color space because the colors must be
added to achieve white. The RGB color model is the way light mixes to produce color.
This is the method digital displays like computer monitors and digital projectors use to
define color. When rgb are set to zero, the resulting color is black because there is no
light. When rgb are set to 1, the resulting color white because all the color values add
up to white. A color value of 0 represents no color where a color value of 1 represents
the full amount of color.
CMYK Color Space
Cyan Magenta Yellow Key(Black)
CMYK is a subtractive color space due to the fact that white is created by removing all color.
CMYK is the standard color space used for printing images. Ink Cartridges in color printers
generally contain four colors of ink, cyan, magenta, yellow, and black. When colored inks are
printed on top of one another they can produce red, green, and blue. When working in 3D
programs CMYK images need to be converted to RGB using and image manipulation
program like Adobe Photoshop or GIMP.
HSV
Hue Saturation Value
Hue is defined as a color location on a color wheel. Hue is represented as an angle on
a circular color palette. Hue values ranges from 0 to 360 where 0 and 360 are equal to
red. Saturation defines a color’s intensity. Saturation ranges from 0 to 1 where 1 is
fullest amount of color. Value defines a color’s brightness. Value ranges from 0 to 1
where 0 is equal to black and 1 is equal to white. The HSV color space is a much more
intuitive color space to work with. In production settings an artist will generally get
color direction in terms of HSV instead of RGB.
Channels
A digital image can be thought of a layer collection of simpler images called channels. If
a pixel in an image can be broken down into RGB components, a channel a digital image
represents all of one component. All of the red components of a digital image make up
the red channel. In addition to color information, channels can be used to store different
types of image data such as depth passes, shadow passes, reflection passes, and matte
passes.
Alpha Channels
Alpha Channels is the fourth channel in the image that is used to store the transparency of
the pixels in an image. Alpha Channels are sometimes referred to as Matte Channels.
Alpha channels are especially important during compositing because it defines what part
of the image needs to be combined with the background image.
Spatial Resolution
The spatial resolution of a digital image is the number of pixels in the image. This is
generally represented by width and height. A 640 x 480 image is comprised of 480
scanlines containing 640 pixels which results in 307,200 pixels in the image. Spatial
resolution is generally what is referred to when someone talks about image size.
Image Standards
SD
640x480
HD 720i
HD 720p
1280x720
HD 1080i
HD 1080p
1920 x1080
2K
2048x1080
4K
4096x2160
Aspect Ratio
The aspect ratio of an image is represented by the image’s width divided by the
height which is generally expressed as x:y where x is width and y is height.
Standard Definition Television has an aspect ration of 4:3 or 1.33:1. High
Definition Television has an aspect ratio of 16:9 or 1.78:1. Feature films
usually have aspect ratios of either 1:85:1 sometimes referred to as flat or 2.39:1
sometimes referred to as scope.
Bit Depth
Bit Depth is a method of measuring the color resolution of a digital image. Bit depth is
sometimes referred to as bits per pixel or bits per channel. The most common bit depth used
for digital images is 8 bit per channel. The deciding factor when determining the bit depth
for a project is performance versus quality. Images with greater bit depths have larger file
sizes and are considerably more difficult to deal with in production, but are sometimes
necessary. Bit depth is extremely important when dealing with film work.
8 bits per
channel
256 possible colors per 256 x 256 x 256
channel
possible colors
16 bits per
channel
65536 possible colors
per channel
16.7 million colors
65536 x 65536 x
281 trillion colors
65536 possible colors
Image Compression
High resolution images can take up a lot of disk space and they become difficult to work
with in a production setting. Image compression schemes use different image processing
techniques to store image data. The final use for the image usually determines the type
of image compression that will be used to store the image data. For images that will
displayed on the web a reduced file size is desirable. The final renders for an animated
film need to retain all possible image detail.
In 1972 engineers working at the USC
Signal and Image Processing Institute
needed an image to test a scanning
process. They used the top portion of a
picture of Playboy centerfold Lena
Soderberg. Since then the 512x512
image has been used as the industry
standard for testing image compression
and manipulation schemes. The image
contains areas of flat color, detailed
texture which makes it and ideal
candidate for testing image processing
techniques. Wikipedia.org
Image from http://sipi.usc.edu/database/database.cgi?volume=misc
Lossless Image Compression
Image compression methods that store image data in such a way that no information is lost
during compression are considered to be lossless. In raw format, all image data is saved per
pixel which is can lead to large file sizes. Lossless image compression formats are methods
of storing the all of image data without any data loss while at the same time reducing file
size.
Run Length Encoding
Run Length Encoding is a simple lossless compression scheme that reduces the size of the
final image by storing sequences in which the same data value occurs in consecutive
pixels as a single data value and count rather than saving each pixel individually.
Lossy Image Compression
During image compression some
methods sacrifice image quality
in order to save disk space.
Once image data is stored using
a lossy compression scheme, a
portion of the original color
information is lost. If the final
use of an image is being
displayed on a website then file
size become important when
determining what image format
to use. If an image is
compressed to 90% of the
original image data at 10% of
the size, the decreased file size
more than compensates for the
lost image data especially since
the loss is almost unnoticeable.
Indexed Color
Indexed color is a compression scheme that limits the number of colors available in the
image to a set number that is saved in a color table. Instead of saving all the color
information per pixel, the pixel data is saved as an index that accesses a position in a the
color table. Since the number of colors available in the image is limited, image data is
lost when converted to an indexed color format. Image formats like .gif and .png use a
version of the indexed color compression scheme to reduce file size.