Image Statistics
Analysis algorithms measuring intensity-based features globally to the input image.
- IntensityExtrema: Computes basic minimum and maximum intensities of an image.
- IntensityStatistics: Computes basic statistics of an image.
- IntensityMaskedStatistics: Computes basic statistics on a region of interest of an image, defined by a binary mask.
- IntensityHistogram: Computes the histogram of a gray level image.
- IntensityBinHistogram: Computes the histogram of a gray level image with a user-defined bin size.
- AutoThresholdingValue: Computes a threshold value partitioning automatically a gray level image into two classes.
- CompareImage: Performs a comparison test between two images and outputs the number of pixels that successfully passed the test.
- CompareValue: Performs a comparison test between an image and value and outputs the number of pixels that successfully passed the test.
- RegionSimilarity: Computes similarity values between the regions from two label images.
- RadialIntensityProfile2d: Computes a radial intensity profile on a 2D image.
- RadialIntensityProfile3d: Computes a radial intensity profile on a 3D image.
- CylindricalIntensityProfile3d: Computes a radial intensity profile on a 3D image by performing a projection along an axis.
- RadialAutocorrelationProfile: Computes the radial autocorrelation function of a grayscale image from its center.
- Cooccurrence2d: Provides texture indicators, also known as Haralick features, based on the computation of co-occurrence matrix.
- MeasureGaussianNoise: Computes an estimation of a gaussian noise standard deviation in an image.
- LocalMaxima2d: Extracts the local maxima of an image using a two-dimensional neighborhood analysis.
- LocalMaxima3d: Extracts the local maxima of an image using a three-dimensional neighborhood analysis.
- LocalDensityMap2d: Measures the local density of a two-dimensional binary image within a binary mask.
- LocalDensityMap3d: Measures the local density of a three-dimensional binary image within a binary mask.
Image Statistics output a global result for an input image, whereas Individual Measurements compute one
result per label of the input image.
For an introduction: Image Analysis
These algorithms extend the set of global shape-based measurements to the gray level based measurements. Features are no longer obtained from binary images, but from gray level, color or multi-channels images, potentially masked by a binary image representing the regions to be considered.
For an introduction: Image Analysis
These algorithms extend the set of global shape-based measurements to the gray level based measurements. Features are no longer obtained from binary images, but from gray level, color or multi-channels images, potentially masked by a binary image representing the regions to be considered.