Is there any brief explanation for each option of Equalization? 

What's the impact of a change on the saturation factor for linear?

1 comment

  • Christian Weise

    The equalization modes define a histogram stretch that will be applied to the raster layers to enhance their appearance. eCognition offers several methods of such contrast adjustment:

    • None = no adjustment

    • Linear = This stretch type applies a linear stretch based on the output minimum and output maximum pixel values, which are used as the endpoints for the histogram. For example, in an 8-bit dataset, the minimum and maximum values could be 33 and 206. A linear stretch is used to distribute the values across 256 values, from 0 to 255. eCognition offers the option to saturate a user-specified percentage (e.g., 5%) of the pixels at each end of the histogram.

    • Standard Deviation = Perform a standard deviation contrast stretch on the range of the lookup table. Often the majority of pixel values fall within an upper and lower limit. Therefore, it makes sense to trim off the extreme values for viewing. You can do this statistically by defining a standard deviation. If you define a 2 standard deviation (my recommendation), the values beyond the 2nd standard deviation become 0 or 255, and the remaining values are stretched between 0 and 255.

    • Gamma Correction = Adjust the range of the lookup table so the output histogram approximates a Gamma distribution. Gamma refers to the degree of contrast between the midlevel gray values of a raster dataset. Gamma does not affect the black or white values in a raster dataset, only the middle values. By applying a gamma correction, you can control the overall brightness of a displayed raster dataset.

    • Histogram = Perform a histogram equalization on the range of the lookup table. It is a nonlinear stretch that redistributes pixel values so that there are approximately the same number of pixels with each value within a range. The result approximates a flat histogram. Therefore, contrast is increased at the peaks of the histogram and lessened at the tails.

    • Manual = Make the range of the lookup table vary linearly from the minimum value to the maximum value.

    Beside our Earth Science history, we have also a Life Science history and these colormaps (here we using not a greyscale lookup table) are a result of it:
    - Hot metal (it colors minimum to maximum pixel values from black to red color)
    - Rainbow (it colors minimum to maximum pixel values from blue to cyan to green to yellow to red; my recommendation to visualize surface layers)

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