liftbase.java

小波提升格式的java源代码

package lift;

import util.*;

/**
  <p>
  class liftbase: base class for simple Lifting Scheme wavelets using
  split, predict, update or update, predict, merge steps.
  </p>

  <p>
  Simple lifting scheme wavelets consist of three steps,
  a split/merge step, predict step and an update step:
  </p>
  <ul>
    <li>
    <p>
    The split step divides the elements in an array so that 
    the even elements are in the first half and the odd
    elements are in the second half.
    </p>
    </li>
    <li>
    <p>
    The merge step is the inverse of the split step.  It takes
    two regions of an array, an odd region and an even region
    and merges them into a new region where an even element 
    alternates with an odd element.
    </p>
    </li>
    <li>
    <p>
    The predict step calculates the difference
    between an odd element and its predicted value based
    on the even elements.  The difference between the
    predicted value and the actual value replaces the
    odd element.
    </p>
    </li>
    <li>
    <p>
    The predict step operates on the odd elements.  The update
    step operates on the even element, replacing them with a
    difference between the predict value and the actual odd element.
    The update step replaces each even element with an average.
    The result of the update step becomes the input to the 
    next recursive step in the wavelet calculation.
    </p>
    </li>

  </ul>

  <p>
  The split and merge methods are shared by all Lifting Scheme wavelet
  algorithms.  This base class provides the transform and inverse
  transform methods (forwardTrans and inverseTrans).  The predict
  and update methods are abstract and are defined for a particular
  Lifting Scheme wavelet sub-class.
  </p>

  <p>
  <b>References:</b>
  </p>

  <ul>
  <li>
  <a 
  href="http://www.bearcave.com/misl/misl_tech/wavelets/lifting/index.html">
  <i>The Wavelet Lifting Scheme</i></a> by Ian Kaplan, www.bearcave.com.
  This is the parent web page for this Java source code.
  </li>
  <li>
  <i>Ripples in Mathematics: the Discrete Wavelet Transform</i> 
  by Arne Jense and Anders la Cour-Harbo, Springer, 2001
  </li>
  <li>
  <i>Building Your Own Wavelets at Home</i> in <a
  href="http://www.multires.caltech.edu/teaching/courses/waveletcourse/">
  Wavelets in Computer Graphics</a>
  </li>
  </ul>

<h4>
   Copyright and Use
</h4>

<p>
   You may use this source code without limitation and without
   fee as long as you include:
</p>
<blockquote>
     This software was written and is copyrighted by Ian Kaplan, Bear
     Products International, www.bearcave.com, 2001.
</blockquote>
<p>
   This software is provided "as is", without any warrenty or
   claim as to its usefulness.  Anyone who uses this source code
   uses it at their own risk.  Nor is any support provided by
   Ian Kaplan and Bear Products International.
<p>
   Please send any bug fixes or suggested source changes to:
<pre>
     [e-mail]
</pre>

  @author Ian Kaplan

 */
public abstract class liftbase {

  /** "enumeration" for forward wavelet transform */
  protected final int forward = 1;
  /** "enumeration" for inverse wavelet transform */
  protected final int inverse = 2;

  /**
    Split the <i>vec</i> into even and odd elements,
    where the even elements are in the first half
    of the vector and the odd elements are in the
    second half.
   */
  protected void split( double[] vec, int N )
  {
    
    int start = 1;
    int end = N - 1;

    while (start < end) {
      for (int i = start; i < end; i = i + 2) {
	double tmp = vec[i];
	vec[i] = vec[i+1];
	vec[i+1] = tmp;
      }
      start = start + 1;
      end = end - 1;
    }
  }

  /**
    Merge the odd elements from the second half of the N element
    region in the array with the even elements in the first
    half of the N element region.  The result will be the
    combination of the odd and even elements in a region
    of length N.
    
   */
  protected void merge( double[] vec, int N )
  {
    int half = N >> 1;
    int start = half-1;
    int end = half;
    
    while (start > 0) {
      for (int i = start; i < end; i = i + 2) {
	double tmp = vec[i];
	vec[i] = vec[i+1];
	vec[i+1] = tmp;
      }
      start = start - 1;
      end = end + 1;
    }
  }


  /** 
    Predict step, to be defined by the subclass

    @param vec input array
    @param N size of region to act on (from 0..N-1)
    @param direction forward or inverse transform

   */
  protected abstract void predict( double[] vec, int N, int direction );

  /** 
    Update step, to be defined by the subclass 

    @param vec input array
    @param N size of region to act on (from 0..N-1)
    @param direction forward or inverse transform

  */
  protected abstract void update(  double[] vec, int N, int direction );


  /**
    <p>
    Simple wavelet Lifting Scheme forward transform
    </p>
    
    <p>
    forwardTrans is passed an array of doubles.  The array size must
    be a power of two.  Lifting Scheme wavelet transforms are calculated
    in-place and the result is returned in the argument array.
    </p>

    <p>
    The result of forwardTrans is a set of wavelet coefficients
    ordered by increasing frequency and an approximate average
    of the input data set in vec[0].  The coefficient bands
    follow this element in powers of two (e.g., 1, 2, 4, 8...).
    </p>
  */
  public void forwardTrans( double[] vec )
  {
    final int N = vec.length;

    for (int n = N; n > 1; n = n >> 1) {
      split( vec, n );
      predict( vec, n, forward );
      update( vec, n, forward );
    }
  } // forwardTrans



  /**
    <p>
    Default two step Lifting Scheme inverse wavelet transform
    </p>

    <p>
    inverseTrans is passed the result of an ordered wavelet 
    transform, consisting of an average and a set of wavelet
    coefficients.  The inverse transform is calculated
    in-place and the result is returned in the argument array.
    </p>

   */
  public void inverseTrans( double[] vec )
  {
    final int N = vec.length;

    for (int n = 2; n <= N; n = n << 1) {
      update( vec, n, inverse );
      predict( vec, n, inverse );
      merge( vec, n );
    }
  } // inverseTrans


} // liftbase