available for processing digital images. They let the user adjust settings that, in the twentieth century, used to rely on the skill of a photographer at the moment of image capture or film development.
Color
Hue. A color is described by its hue,
saturation and value (HSV). Hue is what is normally thought of as color. A digital color in a computer display is a blend of three primary hues: red, green and blue. Saturation is the intensity or dominance of a hue: a hue can be increased or diminished in an image just as black versus white can be adjusted in an image through all shades of gray. Value is the lightness or darkness of a hue and is usually called brightness when the three hues are combined in white light. Image processing software permits the intensity and value of these hues to be adjusted independently within each image.
Conversion to Gray. If the image is
converted to gray scale, as in a report printout, care must be taken that features
of interest remain visible: a fluorescent nondestructive test indication in brilliant green may disappear entirely if it changes to a shade of gray like that in an adjacent area.
Color Balance. The camera setting of
white balance, discussed above, can improve the realism of color photographs by preventing unnatural tints. Image processing programs also enable improvement of color balance. Program menus may refer to it by other terms, such as color intensity or hue saturation.
If a photograph is taken in a digital camera’s RAW file format, image colors can be fixed without information loss. Most cameras take RAW photos in twelve- bit color (4096 shades per color) instead of eight-bit color (256 shades per color), enabling powerful balance adjustments without visible loss in quality.
Size
The more pixels in an image, the more information it carries. An image’s quantity of pixels is its true size in the
dimensionless electronic space of the computer.
To be viewed, the image must be translated to a medium such as a computer display or printed page, where details become visible to human eyes in order to be interpreted. In a process known as scaling, the pixels can be compressed or spread out to fit the desired viewing surface (Fig. 15). Scaling affects resolution, discussed below.
Image size and resolution are usually expressed in terms of image width, in the horizontal dimension. The size and resolution of the vertical scale can be
manipulated independently but to prevent distortion usually undergo the same processes as the horizontal.
The number of pixels in an image can be decreased or increased in a step called resampling or conversion. Resampling cannot add more data to a photograph once it has been shot.
Resolution
The resolution of an image is its ability to distinguish small adjacent objects. Two thin adjacent lines appear as two thin lines, for instance, and not as one thicker line. Resolution depends on the number of pixels in the image and hence on its file size. In Fig. 16, two versions of the same image show the difference between high and low resolution. Details in an image cannot be restored simply by converting it to a higher resolution or from a lossy to a lossless format. Once an image’s resolution is reduced, details are lost. If a display’s resolution exceeds an image’s resolution, the image will look blurry.
Resolution is measured in dots per inch (DPI) for printers or square pixels per inch (PPI) for computer displays, measured along the horizontal axis. Alternatives using SI metric units are to specify pixels per centimeter (pixels·cm–1) or the pixel width in micrometers (µm).
Because the number of pixels in a scalable image is fixed, however, an expression of resolution is meaningless
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Visual Test Imaging
FIGURE15. Example of scaling of digital
images.
228 pixels gives resolution of 58 pixels·cm–1 (144 DPI)
228 pixels gives resolution of 29 pixels·cm–1 (72 DPI)
100 mm (4 in.)
50 mm (2 in.)
Scaling
FIGURE16. Visible light photograph showing magnetic particle indication under
ultraviolet lamp: (a) high resolution, at 40 pixels·cm–1(100 PPI); (b) low resolution, at 10 pixels·cm–1(25 PPI). Lower resolution blurs details. Lowering resolution sometimes enhances contrast or increases hue intensity — side effects better achieved by image processes that do not sacrifice detail.
(a)
unless the viewed image size is also specified. If a given digital image is reduced to half its width, for instance, the number of pixels per unit of width and the resolution are doubled (Fig. 15). The data in the image file may remain the same, but smaller size makes details harder to see. Someone processing digital images must make decisions balancing image size versus resolution.
Brightness
Brightness is the common term for the luminance of light emitted by each pixel. Usually, one control setting adjusts brightness to affect all pixels in an image simultaneously. This parameter can be adjusted to compensate for poor visibility on overcast days. Too little brightness can make a picture dark as night, and too much brightness can make it washed out so no features stand out.
Saturation. In a color image, saturation is
the intensity of a hue. A hue of zero saturation is black or gray. If all three hues
have zero saturation, the image is colorless, black.
Contrast. The setting of contrast controls
the degree of difference between light intensities at different points in the image. Like brightness, contrast is
adjusted to affect all pixels in an image at once. As contrast is increased, for
example, a dark indication becomes easier to see on a bright background and a bright indication becomes more visible on a dark background.
Contrast and brightness interact closely, and the inspector must sometimes adjust them to find the correct settings for each photograph. Figure 17 shows the effect of brightness and contrast on an