Contrast Stretching: Minimum-Maximum Linear Contrast Stretch (Gaussian Stretch) , Percentage Linear Contrast Stretch, Piecewise Linear Contrast Stretch and Non-Linear Contrast Stretch (Especially for GATE-Geospatial 2022)

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There are three methods of linear contrast stretch:

  • Minimum-Maximum Linear Contrast Stretch
  • Percentage Linear Contrast Stretch
  • Piecewise Linear Contrast Stretch

Gaussian Stretch: Minimum-Maximum Linear Contrast Stretch

  • When using the minimum-maximum linear contrast stretch, the original minimum and maximum values of the data are assigned to a newly specified set of values that utilize the full range of available brightness values.
  • Consider an image with a minimum brightness value of 45 and a maximum value of 205. When such an image is viewed without enhancements, the values of 0 to 44 and 206 to 255 are not displayed. Important spectral differences can be detected by stretching the minimum value of 45 to 0 and the maximum value of 120 to 255.
Minimum-Maximum Linear Contrast Enhancement

Minimum-maximum linear contrast enhancement. The minimum and maximum values of the original image are stretched to produce a range of brightness values that use the full capabilities of the image display.

  • An algorithm can be used that matches the old minimum value to the new minimum value and the old maximum value to the new maximum value. All the old intermediate values are scaled proportionately between the new minimum and maximum values.
  • Many digital image processing systems have built-in capabilities that automatically expand the minimum and maximum values to optimize the full range of available brightness values.

Percentage Linear Contrast Stretch

  • The percentage linear contrast stretch is like the minimum-maximum linear contrast stretch except this method uses the specified minimum and maximum values that lie in a certain percentage of pixels from the mean of the histogram.
  • A standard deviation from the mean is often used to push the tails of the histogram beyond the original minimum and maximum values.
Percentage Linear Contrast Stretch
  • It is not necessary that the same percentage be applied to each tail of the histogram distribution. For example, image analysts often need to increase the contrast of an image only at specific portions of the electromagnetic spectrum.
  • An analyst wanting to extract detailed marine information in an image may only be interested in values between 0 and 12. When these values are stretched to 0 and 255, subtle ocean variations can be more easily detected (Figure-B) . A percentage stretch of the same image between values of 25 and 45 yields detailed vegetation information (Figure-C) .
  • This may be useful in the delineation of healthy vegetation. If an analyst is interested in image enhancement for urban features, a percentage linear stretch between the values 40 and 70 in the red gun and 15 to 45 in the green and blue guns will increase the contrast of these features (Figure-D) .
Percentage Linear Contrast Stretch
  • The image (C) continues to stretch the data by applying a one standard deviation percentage linear contrast stretch. The information content of the pixels that saturate at 0 and 255 is lost, yet more detailed analysis of certain aspects of the image may be enhanced for better interpretation. The slope of a percentage linear contrast stretch is much greater than for a simple min-max stretch.
  • Sometimes the same percentage does not need to be applied to each tail of the distribution. The image (D) shows how an analyst would enhance an image if only interested in delineating wetlands. When the values between 13 and 27 are linearly stretched to 0 and 255, all values below 13 become 0 (black) and all values above 27 are set to 255 (white) . This enhancement yields additional information on the smooth grass at the expense at of the rest of the water and upland cover.

Piecewise Linear Contrast Stretch

  • When the distribution of a histogram in an image is bi or trimodal, an analyst may stretch certain values of the histogram for increased enhancement in selected areas. This method of contrast enhancement is called a piecewise linear contrast stretch. A piecewise linear contrast enhancement involves the identification of a number of linear enhancement steps that expands the brightness ranges in the modes of the histogram.
  • Below figure shows the logic used in a normal linear contrast stretch compared to a piecewise linear contrast stretch. In the piecewise stretch, a series of small min-max stretches are set up within a single histogram. Because a piecewise linear contrast stretch is a very powerful enhancement procedure, image analysts must be very familiar with the modes of the histogram and the features they represent in the real world.
Piecewise Linear Contrast Stretch

Nonlinear Contrast Enhancement

  • Nonlinear contrast enhancement often involves histogram equalizations with an algorithm. The nonlinear contrast stretch method has one major disadvantage.
  • Each value in the input image can have several values in the output image so that objects in the original scene lose their correct relative brightness values.

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