public static enum SnakeOptimizerSingle.IntensityNormalizationMode extends Enum<SnakeOptimizerSingle.IntensityNormalizationMode>
For parameter tuning it is of advantage to use normalized image intensities in snake segmentation. As such a normalization can be accomplished in various ways, different modes can be chosen. The image intensities are always scaled to a range of [-1,1], but the base of normalization differs in the different modes.
Enum Constant and Description |
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INTENSITY_NORM_NONE
No normalization of image intensities.
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INTENSITY_NORM_THEORETIC_RANGE
Normalization is done according to the dynamic range of the input
image, i.e. based on the extreme values that can be represented
in the image.
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INTENSITY_NORM_TRUE_RANGE
Normalization is done according to the real intensity range of
the input image, i.e. based on the extreme values found in the
image.
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Modifier and Type | Method and Description |
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static SnakeOptimizerSingle.IntensityNormalizationMode |
valueOf(String name)
Returns the enum constant of this type with the specified name.
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static SnakeOptimizerSingle.IntensityNormalizationMode[] |
values()
Returns an array containing the constants of this enum type, in
the order they are declared.
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public static final SnakeOptimizerSingle.IntensityNormalizationMode INTENSITY_NORM_NONE
public static final SnakeOptimizerSingle.IntensityNormalizationMode INTENSITY_NORM_TRUE_RANGE
public static final SnakeOptimizerSingle.IntensityNormalizationMode INTENSITY_NORM_THEORETIC_RANGE
public static SnakeOptimizerSingle.IntensityNormalizationMode[] values()
for (SnakeOptimizerSingle.IntensityNormalizationMode c : SnakeOptimizerSingle.IntensityNormalizationMode.values()) System.out.println(c);
public static SnakeOptimizerSingle.IntensityNormalizationMode valueOf(String name)
name
- the name of the enum constant to be returned.IllegalArgumentException
- if this enum type has no constant with the specified nameNullPointerException
- if the argument is nullCopyright © 2010–2020 Martin Luther University Halle-Wittenberg, Institute of Computer Science, Pattern Recognition and Bioinformatics. All rights reserved.