com.pearsoneduc.ip.op
Class SeparableGaussianKernel

java.lang.Object
  |
  +--java.awt.image.Kernel
        |
        +--com.pearsoneduc.ip.op.StandardKernel
              |
              +--com.pearsoneduc.ip.op.SeparableGaussianKernel

public class SeparableGaussianKernel
extends StandardKernel

A Kernel for Gaussian blurring. The kernel is one-dimensional, suitable for separable convolution with an image.

Version:
1.1 [1999/07/29]
Author:
Nick Efford

Constructor Summary
SeparableGaussianKernel()
          Creates a separable Gaussian kernel with a default standard deviation of 1.0.
SeparableGaussianKernel(float sigma)
          Creates a separable Gaussian kernel with the specified standard deviation.
 
Method Summary
static float[] createKernelData(float sigma)
          Creates an array of samples from a 1D Gaussian function with the given standard deviation.
static int getSize(float sigma)
          Computes kernel size for a given standard deviation.
static void main(java.lang.String[] argv)
          Creates a SeparableGaussianKernel and writes its coefficients to standard output.
 
Methods inherited from class com.pearsoneduc.ip.op.StandardKernel
createKernel, createKernel, getFractionDigits, setFractionDigits, toString, write
 
Methods inherited from class java.awt.image.Kernel
clone, getHeight, getKernelData, getWidth, getXOrigin, getYOrigin
 
Methods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
 

Constructor Detail

SeparableGaussianKernel

public SeparableGaussianKernel()
Creates a separable Gaussian kernel with a default standard deviation of 1.0.

SeparableGaussianKernel

public SeparableGaussianKernel(float sigma)
Creates a separable Gaussian kernel with the specified standard deviation.
Parameters:
sigma - standard deviation
Method Detail

getSize

public static int getSize(float sigma)
Computes kernel size for a given standard deviation.
Parameters:
sigma - standard deviation
Returns:
kernel size, in pixels.

createKernelData

public static float[] createKernelData(float sigma)
Creates an array of samples from a 1D Gaussian function with the given standard deviation.
Parameters:
sigma - standard deviation
Returns:
array of samples.

main

public static void main(java.lang.String[] argv)
Creates a SeparableGaussianKernel and writes its coefficients to standard output.