boofcv.alg.misc

Class GImageStatistics

java.lang.Object

boofcv.alg.misc.GImageStatistics

public class GImageStatistics
extends java.lang.Object

Generalized version of ImageStatistics. Type checking is performed at runtime instead of at compile type.

Constructor Summary

Constructors

Constructor and Description
GImageStatistics()

Method Summary

Modifier and Type	Method and Description
static void	histogram(ImageSingleBand input, int minValue, int[] histogram) Computes the histogram of intensity values for the image.
static double	max(ImageSingleBand input) Returns the maximum pixel value.
static double	maxAbs(ImageSingleBand input) Returns the absolute value of the element with the largest absolute value.
static <T extends ImageSingleBand> double	mean(T input) Returns the mean pixel intensity value.
static <T extends ImageSingleBand> double	meanDiffAbs(T inputA, T inputB) Computes the mean of the absolute value of the difference between the two images.
static <T extends ImageSingleBand> double	meanDiffSq(T inputA, T inputB) Computes the mean of the difference squared between the two images.
static double	min(ImageSingleBand input) Returns the minimum pixel value.
static <T extends ImageSingleBand> double	sum(T input) Returns the sum of all the pixels in the image.
static <T extends ImageSingleBand> double	variance(T input, double mean) Computes the variance of pixel intensity values inside the image.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

GImageStatistics

public GImageStatistics()

Method Detail

maxAbs

public static double maxAbs(ImageSingleBand input)

Returns the absolute value of the element with the largest absolute value.

Parameters:

input - Input image. Not modified.

Returns:

Largest pixel absolute value.

max

public static double max(ImageSingleBand input)

Returns the maximum pixel value.

Parameters:

input - Input image. Not modified.

Returns:

Maximum pixel value.

min

public static double min(ImageSingleBand input)

Returns the minimum pixel value.

Parameters:

input - Input image. Not modified.

Returns:

Minimum pixel value.

sum

public static <T extends ImageSingleBand> double sum(T input)

Returns the sum of all the pixels in the image.

Parameters:

input - Input image. Not modified.

Returns:

Sum of pixel intensity values

mean

public static <T extends ImageSingleBand> double mean(T input)

Returns the mean pixel intensity value.

Parameters:

input - Input image. Not modified.

Returns:

Mean pixel value

variance

public static <T extends ImageSingleBand> double variance(T input,
                                                          double mean)

Computes the variance of pixel intensity values inside the image.

Parameters:

input - Input image. Not modified.

mean - Mean pixel intensity value.

Returns:

Pixel variance

meanDiffSq

public static <T extends ImageSingleBand> double meanDiffSq(T inputA,
                                                            T inputB)

Computes the mean of the difference squared between the two images.

Parameters:

inputA - Input image. Not modified.

inputB - Input image. Not modified.

Returns:

Mean difference squared

meanDiffAbs

public static <T extends ImageSingleBand> double meanDiffAbs(T inputA,
                                                             T inputB)

Computes the mean of the absolute value of the difference between the two images.

Parameters:

inputA - Input image. Not modified.

inputB - Input image. Not modified.

Returns:

Mean absolute difference

histogram

public static void histogram(ImageSingleBand input,
                             int minValue,
                             int[] histogram)

Computes the histogram of intensity values for the image. For floating point images it is rounded to the nearest integer using "(int)value".

Parameters:

input - (input) Image.

minValue - (input) Minimum possible intensity value Ignored for unsigned images.

histogram - (output) Storage for histogram. Number of elements must be equal to max value.