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A common problem in remote sensing is that the range of reflectance values collected by a sensor may not match the capabilities of the film or color display monitor. Materials on the Earth's surface reflect and emit different amounts of energy. A sensor might record a tremendous amount of energy from a one material in a certain wavelength, while another material is recorded at much less energy in the same wavelength. Image enhancement techniques make an image easier to analyze and interpret. The range of brightness values present on an image is referred to as contrast. Contrast enhancement is a process that makes the image features stand out more clearly by making optimal use of the colors available on the display or output device.
Contrast manipulations involve changing the range of values in an image in order to increase contrast. For example, an image might start with a range of values between 40 and 90. When this is stretched to a range of 0 to 255, the differences between features is accentuated. Unfortunately, different features often reflect similar amounts of energy throughout the electromagnetic spectrum, resulting in a relatively low contrast image. In addition, besides the obvious low contrast characteristics of biophysical materials, there are cultural factors at work. For example, people in developing countries often use natural building materials (e.g., wood and soil) in the construction of urban areas (Haack et al., 1995). This results in remotely sensed imagery with a much lower contrast as opposed to urban areas in developed countries where concrete, asphalt. and fertilized green vegetation may be more prevalent (Jensen, 1996). Thus, it is important to consider both the biophysical and human components when enhancing an image for maximum contrast.
The sensitivity of the sensor is another factor to consider when creating low-contrast remotely sensed imagery. Most sensors today are equipped with detectors that are designed to record a relatively wide range of unsaturated scene brightness values (e.g., 0 to 255). When an image becomes saturated, the radiometric sensitivity of the detector is insufficent to record the full range of intensities of reflected or emitted energy emanating from the scene. Naturally occurring materials on the earth have a wide range of spectral properties. Satellite detectors must be sensitive to low reflectance material, such as dark volcanic basalt, as well as high reflectance material such as fields of snow. However, most of real world remote sensing applications involve few scenes that are composed of brightness values which utilize the full sensitivity range of satellite detectors. Such scenes are relatively low-contrasting with brightness values ranging from 0 to 100.
As mentioned before, the contrast of an image can be increased by utilizing the entire brightness range of a display or hard-copy output device. Digital methods generally produce a more satisfactory contrast enhancement because of the precision and wide variety of processes that can be applied to the imagery. Linear and nonlinear digital techniques are two widely practiced methods of increasing the contrast of an image.
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ERDAS, Inc., 1995, Overview of ERDAS IMAGINE 8.2, ERDAS, Inc. Atlanta, Georgia, pp. 25-35.
Haack, B., J. R. Jensen, and R. A. Welch, 1995, "Urban-Suburban Analysis," Manual of Photographic Interpretation, 2nd ed., W. Phillipson, ed. Bethesda, MD: American Society for Photogrammetry and Remote Sensing.
Jensen, J. R., 1996, Introductory Digital Image Processing: A remote sensing perspective, 2nd Edition. NJ: Prentice-Hall, pp. 141-152.
