`
`Written by Jonathan Sachs
`Copyright © 1996-1999 Digital Light & Color
`
`Introduction
`
`When using digital equipment to capture, store, modify and view photographic
`images, they must first be converted to a set of numbers in a process called digitiza-
`tion or scanning. Computers are very good at storing and manipulating numbers, so
`once your image has been digitized you can use your computer to archive, examine,
`alter, display, transmit, or print your photographs in an incredible variety of ways.
`
`Pixels and Bitmaps
`
`Digital images are composed of pixels (short for picture elements). Each pixel rep-
`resents the color (or gray level for black and white photos) at a single point in the
`image, so a pixel is like a tiny dot of a particular color. By measuring the color of an
`image at a large number of points, we can create a digital approximation of the image
`from which a copy of the original can be reconstructed. Pixels are a little like grain
`particles in a conventional photographic image, but arranged in a regular pattern of
`rows and columns and store information somewhat differently. A digital image is a
`rectangular array of pixels sometimes called a bitmap.
`
`Digital Image Basics
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`Digital Image Basics
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`Types of Digital Images
`
`For photographic purposes, there are two important types of digital images—color
`and black and white. Color images are made up of colored pixels while black and
`white images are made of pixels in different shades of gray.
`
`Black and White Images
`A black and white image is made up of pixels each of which holds a single number
`corresponding to the gray level of the image at a particular location. These gray lev-
`els span the full range from black to white in a series of very fine steps, normally
`256 different grays. Since the eye can barely distinguish about 200 different gray
`levels, this is enough to give the illusion of a stepless tonal scale as illustrated
`below:
`
`Assuming 256 gray levels, each black and white pixel can be stored in a single byte
`(8 bits) of memory.
`
`Color Images
`A color image is made up of pixels each of which holds three numbers correspond-
`ing to the red, green, and blue levels of the image at a particular location. Red,
`green, and blue (sometimes referred to as RGB) are the primary colors for mixing
`light—these so-called additive primary colors are different from the subtractive pri-
`mary colors used for mixing paints (cyan, magenta, and yellow). Any color can be
`created by mixing the correct amounts of red, green, and blue light. Assuming 256
`levels for each primary, each color pixel can be stored in three bytes (24 bits) of
`memory. This corresponds to roughly 16.7 million different possible colors.
`
`Note that for images of the same size, a black and white version will use three times
`less memory than a color version.
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`Digital Image Basics
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`Types of Digital Images
`
`Binary or Bilevel Images
`
`Binary images use only a single bit to represent each pixel. Since a bit can only
`exist in two states—on or off, every pixel in a binary image must be one of two col-
`ors, usually black or white. This inability to represent intermediate shades of gray is
`what limits their usefulness in dealing with photographic images.
`
`Indexed Color Images
`
`Some color images are created using a limited palette of colors, typically 256 dif-
`ferent colors. These images are referred to as indexed color images because the data
`for each pixel consists of a palette index indicating which of the colors in the palette
`applies to that pixel. There are several problems with using indexed color to repre-
`sent photographic images. First, if the image contains more different colors than are
`in the palette, techniques such as dithering must be applied to represent the missing
`colors and this degrades the image. Second, combining two indexed color images
`that use different palettes or even retouching part of a single indexed color image
`creates problems because of the limited number of available colors.
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`Digital Image Basics
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`Digital Image Basics
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`Resolution
`
`The more points at which we sample the image by measuring its color, the more
`detail we can capture. The density of pixels in an image is referred to as its resolu-
`tion. The higher the resolution, the more information the image contains. If we keep
`the image size the same and increase the resolution, the image gets sharper and
`more detailed. Alternatively, with a higher resolution image, we can produce a
`larger image with the same amount of detail.
`
`For example, the following images illustrate what happens as we reduce the resolu-
`tion of an image while keeping its size the same—the pixels get larger and larger
`and there is less and less detail in the image:
`
`Original (400x262)
`
`Half Size (200x131)
`
`Quarter Size (100x65)
`
`Eighth Size (50x32)
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`Color Terminology
`
`As we reduce the resolution of an image while keeping its pixels the same size—the
`image gets smaller and smaller while the amount of detail (per square inch) stays the
`same:
`
`Color Terminology
`
`While pixels are normally stored within the computer according to their red, green,
`and blue levels, this method of specifying colors (sometimes called the RGB color
`space) does not correspond to the way we normally perceive and categorize colors.
`There are many different ways to specify colors, but the most useful ones work by
`separating out the hue, saturation, and brightness components of a color.
`
`Primary and Secondary Colors and Additive and Subtractive Color
`Mixing
`
`Primary colors are those that cannot be created by mixing other colors. Because of
`the way we perceive colors using three different sets of wavelengths, there are three
`primary colors. Any color can be represented as some mixture of these three pri-
`mary colors.
`
`There are two different ways to combine colors—additive and subtractive color
`mixing.
`
`Subtractive color mixing is the one most of us learned in school, and it describes
`how two colored paints or inks combine on a piece of paper. The three subtractive
`
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`primaries are Cyan (blue-green), Magenta (purple-red), and Yellow (not Blue, Red,
`and Yellow as we were taught).
`
`Additive color mixing refers to combining lights of two different colors, for exam-
`ple by shining two colored spotlights on the same white wall. The additive color
`model is the one used in computer displays as the image is formed on the face of the
`monitor by combining beams of red, green, and blue light in different proportions.
`
`Color printers use the subtractive color model and use cyan, magenta, and yellow
`inks. To compensate for the impure nature of most printing inks, a fourth color,
`black is also used since the black obtained by combining cyan, magenta, and yellow
`inks is often a murky dark green rather than a deep, rich black. For this and other
`reasons, commercial color printing presses use a 4-color process to reproduce color
`images in magazines.
`
`A color created by mixing equal amounts of two primary colors is called a second-
`ary. In the additive color system, the primary colors are:
`
`IRed
`
`IGreen IBlue
`
`and the secondary colors are:
`
`ICyan IMagenta IYellow
`
`In the subtractive color system, the roles of the primaries and secondaries are
`reversed.
`
`Color Gamut
`In the real world, the ideal of creating any visible color by mixing three primary
`colors is never actually achieved. The dyes, pigments, and phosphors used to create
`colors on paper or computer screens are imperfect and cannot recreate the full range
`of visible colors. The actual range of colors achievable by a particular device or
`medium is called its color gamut and this is mostly but not entirely determined by
`the characteristics of its primary colors. Since different devices such as computer
`monitors, printers, scanners, and photographic film all have different color gamuts,
`the problem of achieving consistent color is quite challenging. Different media also
`differ in their total dynamic range—how dark is the darkest achievable black and
`how light is the brightest white.
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`Color Terminology
`
`Color Management
`The process of getting an image to look the same between two or more different
`media or devices is called color management, and there are many different color
`management systems available today. Unfortunately, most are complex, expensive,
`and not available for a full range of devices.
`
`Hue
`The hue of a color identifies what is commonly called “color”. For example, all reds
`have a similar hue value whether they are light, dark, intense, or pastel.
`
`Saturation
`The saturation of a color identifies how pure or intense the color is. A fully satu-
`rated color is deep and brilliant—as the saturation decreases, the color gets paler
`and more washed out until it eventually fades to neutral.
`
`Brightness
`The brightness of a color identifies how light or dark the color is. Any color whose
`brightness is zero is black, regardless of its hue or saturation. There are different
`schemes for specifying a color's brightness and depending on which one is used, the
`results of lightening a color can vary considerably.
`
`Luminance
`The luminance of a color is a measure of its perceived brightness. The computation
`of luminance takes into account the fact that the human eye is far more sensitive to
`certain colors (like yellow-green) than to others (like blue).
`
`Chrominance
`Chrominance is a complementary concept to luminance. If you think of how a tele-
`vision signal works, there are two components—a black and white image which
`represents the luminance and a color signal which contains the chrominance infor-
`mation. Chrominance is a 2-dimensional color space that represents hue and satura-
`tion, independent of brightness.
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`Digital Image Basics
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`Viewing Images on a Monitor
`
`Before you can get consistent results working with digital images, you must create
`a standard viewing environment.
`
`Most computer monitors use a standard set of phosphors (the chemical compounds
`on the face of the screen that are responsible for creating its primary colors). These
`phosphors, combined with the electronic circuitry that activates them create color
`images on your computer screen. To get an accurate match between what you see
`on your monitor and prints or other output requires that a number of variables be
`controlled:
`
`Viewing Conditions
`First, it is very important for critical evaluation of photographic images on a com-
`puter monitor to work in an environment with subdued lighting. When strong room
`light falls on the face of the monitor, it makes it almost impossible to discern
`shadow detail and seriously alters the appearance of many of the colors.
`
`Monitor Brightness Control
`Next, you must set the brightness control on your monitor correctly. If the level is
`too high, blacks will start to become grays and colors will be washed out. If the
`level is too low, there will be loss of shadow detail and colors will appear murky.
`
`Gamma
`Since the human eye has a nonlinear response curve (it is more sensitive to varia-
`tions in low light than to an equal variation in bright light), it is important to track
`this nonlinearity with the display of different gray levels. The curve that relates the
`amount of light emitted from the monitor to the 256 different gray levels in the dig-
`ital image is called the gamma curve. There are several different standard gamma
`curves in common use. They all follow a power law of the following form:
`
`γ
`
`b = v
`
`where b is the brightness of the light emitted from the screen, v is the gray level
`value in the image and γ is the monitor gamma. The standard value for γ that most
`closely approximates the response of the human eye is 2.22. This is the value used
`by the television industry for storing and displaying video images. The prepress
`
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`Viewing Images on a Monitor
`
`industry has standardized on a value of 1.8 which more closely corresponds to the
`characteristics of printing presses. Macintosh computers often use the value 1.4 for
`some unknown reason, while most uncorrected PC monitors have a gamma of about
`2.3.
`
`If an image was designed to be displayed on a monitor with a gamma of 2.2 and the
`monitor's actual gamma is set to 1.8, the image will appear too light and washed
`out. Conversely, if an image was adjusted to look good using a computer with a
`monitor gamma of 1.4 or 1.8 and viewed at 2.2, it will look too dark. For this rea-
`son, it is very important to set your computer's monitor to the same gamma setting
`as will be used to print it. If gamma is ignored, there is no way to guarantee that
`prints will not be too light or too dark.
`
`White Point
`Finally, there is an important characteristic of computer monitors called white
`point. This is usually given as a color temperature and for most uncorrected moni-
`tors, it run about 9300 degrees. What this means is that the white that is displayed
`on the monitor when you send it maximum values of red, green, and blue has a dis-
`tinctly bluish cast. If you were going to view your prints under a light of this same
`color temperature, you would get a good match (all other variables being set prop-
`erly). Different lights like incandescent, quartz halogen, fluorescent, and daylight
`(morning, evening, indirect, etc.) all have different color temperatures and prints
`viewed using these different lighting conditions will look radically different. The
`standard white point used in the graphic arts industry is a 5000 degree color temper-
`ature and most light boxes are set to roughly this color. Viewing prints under fluo-
`rescent lighting can be particularly deceptive as mercury vapor lamps has several
`spikes in the green part of the spectrum whereas daylight has a relatively smooth
`spectrum. This can give rise to considerable variation in certain colors.
`
`Two monitors which use the same phosphors, are both viewed in subdued light,
`have their gamma set the same, have their brightness control set properly, and have
`the same white point, should produce nearly identical displays.
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`Color Spaces
`
`A color space is a mathematical system for representing colors. Since it takes at
`least three independent measurements to determine a color, most color spaces are
`three-dimensional. Many different color spaces have been created over the years in
`an effort to categorize the full gamut of possible colors according to different char-
`acteristics. Picture Window uses three different color spaces:
`
`RGB
`Most computer monitors work by specifying colors according to their red, green,
`and blue components. These three values define a 3-dimensional color space call
`the RGB color space. The RGB color space can be visualized as a cube with red
`varying along one axis, green varying along the second, and blue varying along the
`third. Every color that can be created by mixing red, green, and blue light is located
`somewhere within the cube. The following images show the outside of the RGB
`cube viewed from two different directions:
`
`The eight corners of the cube correspond to the three primary colors (Red, Green,
`Blue), the three secondary colors (Cyan, Magenta, Yellow) and black and white. All
`the different neutral grays are located on the diagonal of the cube that connects the
`black and the white vertices.
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`Color Spaces
`
`HSV (Hue Saturation Value)
`The HSV color space attempts to characterize colors according to their hue, satura-
`tion, and value (brightness). This color space is based on a so-called hexcone model
`which can be visualized as a prism with a hexagon on one end that tapers down to a
`single point at the other. The hexagonal face of the prism is derived by looking at
`the RGB cube centered on its white corner. The cube, when viewed from this angle,
`looks like a hexagon with white in the center and the primary and secondary colors
`making up the six vertices of the hexagon. This color hexagon is the one Picture
`Window uses in its color picker to display the brightest possible versions of all pos-
`sible colors based on their hue and saturation. Successive crossections of the HSV
`hexcone as it narrows to its vertex are illustrated below showing how the colors get
`darker and darker, eventually reaching black.
`
`V = 100%
`
`V = 75%
`
`V = 50%
`
`V = 25%
`
`HSL (Hue Saturation Lightness)
`The HSL color space (also sometimes called HSB) attempts to characterize colors
`according to their hue, saturation, and lightness (brightness). This color space is
`based on a double hexcone model which consists of a hexagon in the middle that
`converges down to a point at each end. Like the HSV color space, the HSL space
`
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`goes to black at one end, but unlike HSV, it tends toward white at the opposite end.
`The most saturated colors appear in the middle. Note that unlike in the HSL color
`space, this central crossection has 50% gray in the center and not white.
`
`L = 25%
`
`L = 50%
`
`L = 75%
`
`Continuous Tone vs. Halftone Images
`
`There are many different technologies used to reproduce photographic images.
`Some printing technologies such as laser and ink jet printers work by creating indi-
`vidual dots, each of which is one of a small number of solid colors. For example, a
`black and white laser printer can only print black or white pixels -- it cannot pro-
`duce gray dots. To create the illusion of a photographic image, these tiny dots must
`be clustered in different proportions to reproduce the different colors and gray lev-
`els in the image. This dot clustering process is called halftoning or dithering and it
`can be done in many different ways.
`
`continuous tone
`image
`
`ordered dither
`halftone
`
`error diffusion
`halftone
`
`Devices such as computer monitors, dye sublimation printers, and film recorders can
`create dots of any color without halftoning, and these are called continuous tone
`printers because they can reproduce a continuous range of gray levels or colors.
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`How images are digitized
`
`Because a continuous tone printer packs more information into each dot, to achieve
`comparable image quality, printers that use halftoning or dithering require higher
`resolution, by a factor of roughly 6-8. Thus a continuous tone printer that outputs
`images at 200 dpi is roughly similar in quality to a halftone printer that outputs pix-
`els at roughly 1200-1600 dpi. For this reason, even a 600 dpi laser printer makes
`relatively coarse images equivalent to only about 75 dpi continuous tone output.
`
`For printed output to appear photographic when viewed from a standard distance of
`about 10 inches requires between 150 and 300 dpi. At 150 dpi, most images will
`appear noticeable soft, while between 200 and 300 dpi the incremental improve-
`ment is quite small. Beyond 300 dpi there is still some improvement, but for most
`images and most observers, it will be virtually unnoticeable.
`
`How images are digitized
`
`The process of converting an image to pixels is called digitizing or scanning and
`this function can be performed in many different ways.
`
`Film Scanners
`This type of scanner is sometimes called a slide or transparency scanner. They are
`specifically designed for scanning film, usually 35mm slides or negatives, but some
`of the more expensive ones can also scan medium and large format film. These
`scanners work by passing a narrowly focused beam of light through the film and
`reading the intensity and color of the light that emerges.
`
`Flatbed Scanners
`This type of scanner is sometimes called a reflective scanner. They are designed for
`scanning prints or other flat, opaque materials. These scanners work by shining
`white light onto the object and reading the intensity and color of the light that is
`reflected from it, usually a line at a time. Some flatbed scanners have available
`transparency adapters, but for a number of reasons, in most cases these are not very
`well suited to scanning film. On the other hand, flatbed scanners can be used as a
`sort of lensless camera to directly digitize flat objects like leaves.
`
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`Digital Cameras
`One of the most direct ways to capture an image is a digital camera which uses a
`special semiconductor chip called a CCD (charge coupled device) to convert light
`to electrical signals right at the image plane. The quality of the images created in
`this manner is closely related to the number of pixels the CCD can capture. Afford-
`able digital cameras suffer from relatively low resolution, limited dynamic range,
`and low ISO film speed equivalent, and consequently do not always produce high
`quality digital images. To get images with quality comparable to film photography
`currently requires very expensive digital cameras.
`
`Video Frame Grabbers
`This type of scanner uses a video camera to capture a scene or object and then con-
`verts the video signal that comes out of the camera to a digital image in your com-
`puter memory. A video camera can be used to digitize scenes containing 3-
`dimensional objects, but they usually have much lower image quality than film or
`flatbed scanners.
`
`Scanning Services
`Photo CD is a service started by Kodak a number of years ago whereby your film
`can be scanned using a high quality scanner and written to a compact disk you com-
`puter can access. Using Photo CD service is an inexpensive way to get high quality
`scans of your images without purchasing a scanner.
`
`Many other scanning services are available which can scan prints or film to floppy
`disks or removable disk cartridges. These vary from low resolution snapshot quality
`images to professional drum scans at very high resolution.
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