The digital representation of visual information. Digital Images. 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
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The digital representation of visual information.
The method in which visual information is captured and converted into digital images can be broken down into three categories.
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.
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.
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 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.
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.
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 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.
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.
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 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.
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
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 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.
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 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.