Uses of Class
net.imglib2.algorithm.convolution.kernel.Kernel1D

Packages that use Kernel1D

Package	Description
net.imglib2.algorithm.blocks.convolve
net.imglib2.algorithm.convolution.kernel

Uses of Kernel1D in net.imglib2.algorithm.blocks.convolve

Methods in net.imglib2.algorithm.blocks.convolve with parameters of type Kernel1D

Modifier and Type	Method and Description
static <T extends net.imglib2.type.NativeType<T>> UnaryBlockOperator<T,T>	Convolve.createOperator(T type, ComputationType computationType, ClampType clampType, Kernel1D[] kernels) Create a UnaryBlockOperator to convolve with the given kernels.

Uses of Kernel1D in net.imglib2.algorithm.convolution.kernel

Methods in net.imglib2.algorithm.convolution.kernel that return Kernel1D

Modifier and Type	Method and Description
static Kernel1D[]	Kernel1D.asymmetric(double[][] fullKernels, int[] originIndices) Similar to asymmetric(double[], int) but creates an array of one-dimensional convolution kernels.
static Kernel1D	Kernel1D.asymmetric(double[] fullKernel, int originIndex) Creates a one-dimensional asymmetric convolution kernel.
static Kernel1D	Kernel1D.centralAsymmetric(double... kernel) Creates a one-dimensional asymmetric convolution kernel, where the origin of the kernel is in the middle.
static Kernel1D[]	Kernel1D.centralAsymmetric(double[][] kernels) Similar to centralAsymmetric(double...) but creates an array of one-dimensional convolution kernels.
static Kernel1D	Kernel1D.symmetric(double... halfKernel) Creates a one-dimensional symmetric convolution kernel.
static Kernel1D[]	Kernel1D.symmetric(double[][] halfKernels) Similar to symmetric(double[]) but creates an array of one-dimensional convolution kernels.

Methods in net.imglib2.algorithm.convolution.kernel with parameters of type Kernel1D

Modifier and Type	Method and Description
static Convolution<net.imglib2.type.numeric.NumericType<?>>	SeparableKernelConvolution.convolution(Kernel1D... kernels) Return an object, that performs the separable convolution with the given kernel.
static Convolution<net.imglib2.type.numeric.NumericType<?>>	SeparableKernelConvolution.convolution1d(Kernel1D kernel, int direction) Apply a convolution only in one dimension.
static void	SeparableKernelConvolution.convolve(Kernel1D[] kernels, net.imglib2.RandomAccessible<? extends net.imglib2.type.numeric.NumericType<?>> source, net.imglib2.RandomAccessibleInterval<? extends net.imglib2.type.numeric.NumericType<?>> target) Convolve source with a separable kernel and write the result to output.

Constructors in net.imglib2.algorithm.convolution.kernel with parameters of type Kernel1D

Constructor and Description
ConvolverNativeType(Kernel1D kernel, net.imglib2.RandomAccess<? extends T> in, net.imglib2.RandomAccess<? extends T> out, int d, long lineLength)
ConvolverNumericType(Kernel1D kernel, net.imglib2.RandomAccess<? extends T> in, net.imglib2.RandomAccess<? extends T> out, int d, long lineLength)
DoubleConvolverRealType(Kernel1D kernel, net.imglib2.RandomAccess<? extends net.imglib2.type.numeric.RealType<?>> in, net.imglib2.RandomAccess<? extends net.imglib2.type.numeric.RealType<?>> out, int d, long lineLength)
FloatConvolverRealType(Kernel1D kernel, net.imglib2.RandomAccess<? extends net.imglib2.type.numeric.RealType<?>> in, net.imglib2.RandomAccess<? extends net.imglib2.type.numeric.RealType<?>> out, int d, long lineLength)
KernelConvolverFactory(Kernel1D kernel)