net.imglib2.algorithm.metrics.imagequality

Class MSE

java.lang.Object

net.imglib2.algorithm.metrics.imagequality.MSE

public class MSE
extends Object

Compute the mean squared error (MSE) between a reference and a processed image. The metrics runs on the whole image, whether 2D or 3D. In order to get individual slice MSE, run the metrics on each slice independently.

Author:

Joran Deschamps

Constructor Summary

Constructors

Constructor and Description
MSE()

Method Summary

Modifier and Type	Method and Description
static <T extends net.imglib2.type.numeric.RealType<T>> double	computeMetrics(net.imglib2.RandomAccessibleInterval<T> reference, net.imglib2.RandomAccessibleInterval<T> processed) Compute the mean squared error (MSE) score between reference and processed images.

Methods inherited from class java.lang.Object

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

Constructor Detail

MSE

public MSE()

Method Detail

computeMetrics

public static <T extends net.imglib2.type.numeric.RealType<T>> double computeMetrics(net.imglib2.RandomAccessibleInterval<T> reference,
                                                                                     net.imglib2.RandomAccessibleInterval<T> processed)

Compute the mean squared error (MSE) score between reference and processed images. The metrics run on the whole image (regardless of the dimensions).

Type Parameters:

T - Type of the image pixels

Parameters:

reference - Reference image

processed - Processed image

Returns:

Metrics score