/* DCT.java --
Copyright (C) 2005 Free Software Foundation, Inc.
This file is part of GNU Classpath.
GNU Classpath is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2, or (at your option)
any later version.
GNU Classpath is distributed in the hope that it will be useful, but
WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
General Public License for more details.
You should have received a copy of the GNU General Public License
along with GNU Classpath; see the file COPYING. If not, write to the
Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA
02110-1301 USA.
Linking this library statically or dynamically with other modules is
making a combined work based on this library. Thus, the terms and
conditions of the GNU General Public License cover the whole
combination.
As a special exception, the copyright holders of this library give you
permission to link this library with independent modules to produce an
executable, regardless of the license terms of these independent
modules, and to copy and distribute the resulting executable under
terms of your choice, provided that you also meet, for each linked
independent module, the terms and conditions of the license of that
module. An independent module is a module which is not derived from
or based on this library. If you modify this library, you may extend
this exception to your version of the library, but you are not
obligated to do so. If you do not wish to do so, delete this
exception statement from your version. */
package gnu.javax.imageio.jpeg;
/**
* Discrete Cosine Transformations.
*/
public class DCT
{
/**
* Cosine matrix
*/
public double c[][] = new double[8][8];
/**
* Transformed cosine matrix
*/
public double cT[][] = new double[8][8];
public DCT()
{
initMatrix();
}
/**
* Figure A.3.3 IDCT, Cu Cv on A-5 of the ISO DIS 10918-1. Requirements and
* Guidelines.
*
* @param u
* @return
*/
public static double C(int u)
{
return ((u == 0) ? (double) 1 / (double) Math.sqrt((double) 2)
: (double) 1);
}
/**
* Initialize matrix values for the fast_idct function
*/
private void initMatrix()
{
for (int j = 0; j < 8; j++)
{
double nn = (double) (8);
c[0][j] = 1.0 / Math.sqrt(nn);
cT[j][0] = c[0][j];
}
for (int i = 1; i < 8; i++)
{
for (int j = 0; j < 8; j++)
{
double jj = (double) j;
double ii = (double) i;
c[i][j] =
Math.sqrt(2.0 / 8.0)
* Math.cos(((2.0 * jj + 1.0) * ii * Math.PI) / (2.0 * 8.0));
cT[j][i] = c[i][j];
}
}
}
/**
* slow_idct - Figure A.3.3 IDCT (informative) on A-5 of the ISO DIS
* 10918-1. Requirements and Guidelines. This is a slow IDCT, there are
* better algorithms to use, it's fairly expensive with processor speed.
*
* @param matrix
* @return
*/
public static double[][] slow_idct(double[][] matrix)
{
double[][] output = new double[matrix.length][matrix.length];
for (int y = 0; y < 8; y++)
{
for (int x = 0; x < 8; x++)
{
double val = 0;
for (double v = 0; v < 8; v++)
{
double innerloop = 0;
for (double u = 0; u < 8; u++)
innerloop += (DCT.C((int) u) / (double) 2)
* matrix[(int) v][(int) u]
* Math.cos((2 * x + 1) * u * Math.PI / (double) 16)
* Math.cos((2 * y + 1) * v * Math.PI / (double) 16);
val += (DCT.C((int) v) / (double) 2) * innerloop;
}
output[y][x] = (val + 128);
}
}
return (output);
}
public static float[][] slow_fdct(float[][] value)
{
float[][] buffer = new float[8][8];
for (int u = 0; u < 8; u++)
{
for (int v = 0; v < 8; v++)
{
buffer[u][v] =
(float) (1 / 4) * (float) C((int) u) * (float) C((int) v);
float innerval = 0;
for (int x = 0; x < 8; x++)
{
for (int y = 0; y < 8; y++)
{
innerval += value[y][x]
* Math.cos(((2 * x + 1) * u * Math.PI) / 16)
* Math.cos(((2 * y + 1) * v * Math.PI) / 16);
}
}
buffer[u][v] *= innerval;
}
}
return (buffer);
}
public float[][] fast_fdct(float[][] input)
{
float output[][] = new float[8][8];
double temp[][] = new double[8][8];
double temp1;
int i;
int j;
int k;
for (i = 0; i < 8; i++)
{
for (j = 0; j < 8; j++)
{
temp[i][j] = 0.0;
for (k = 0; k < 8; k++)
{
temp[i][j] += (((int) (input[i][k]) - 128) * cT[k][j]);
}
}
}
for (i = 0; i < 8; i++)
{
for (j = 0; j < 8; j++)
{
temp1 = 0.0;
for (k = 0; k < 8; k++)
{
temp1 += (c[i][k] * temp[k][j]);
}
output[i][j] = (int) Math.round(temp1) * 8;
}
}
return output;
}
/**
* fast_idct - Figure A.3.3 IDCT (informative) on A-5 of the ISO DIS
* 10918-1. Requires and Guidelines. This is a fast IDCT, it much more
* effecient and only inaccurate at about 1/1000th of a percent of values
* analyzed. Cannot be static because initMatrix must run before any
* fast_idct values can be computed.
*
* @param input
* @return
*/
public double[][] fast_idct(double[][] input)
{
double output[][] = new double[8][8];
double temp[][] = new double[8][8];
double temp1;
int i, j, k;
for (i = 0; i < 8; i++)
{
for (j = 0; j < 8; j++)
{
temp[i][j] = 0.0;
for (k = 0; k < 8; k++)
{
temp[i][j] += input[i][k] * c[k][j];
}
}
}
for (i = 0; i < 8; i++)
{
for (j = 0; j < 8; j++)
{
temp1 = 0.0;
for (k = 0; k < 8; k++)
temp1 += cT[i][k] * temp[k][j];
temp1 += 128.0;
if (temp1 < 0)
output[i][j] = 0;
else if (temp1 > 255)
output[i][j] = 255;
else
output[i][j] = (int) Math.round(temp1);
}
}
return output;
}
public double[][] idj_fast_fdct(float input[][])
{
double output[][] = new double[8][8];
double tmp0, tmp1, tmp2, tmp3, tmp4, tmp5, tmp6, tmp7;
double tmp10, tmp11, tmp12, tmp13;
double z1, z2, z3, z4, z5, z11, z13;
int i;
int j;
// Subtracts 128 from the input values
for (i = 0; i < 8; i++)
{
for (j = 0; j < 8; j++)
{
output[i][j] = ((double) input[i][j] - (double) 128.0);
// input[i][j] -= 128;
}
}
for (i = 0; i < 8; i++)
{
tmp0 = output[i][0] + output[i][7];
tmp7 = output[i][0] - output[i][7];
tmp1 = output[i][1] + output[i][6];
tmp6 = output[i][1] - output[i][6];
tmp2 = output[i][2] + output[i][5];
tmp5 = output[i][2] - output[i][5];
tmp3 = output[i][3] + output[i][4];
tmp4 = output[i][3] - output[i][4];
tmp10 = tmp0 + tmp3;
tmp13 = tmp0 - tmp3;
tmp11 = tmp1 + tmp2;
tmp12 = tmp1 - tmp2;
output[i][0] = tmp10 + tmp11;
output[i][4] = tmp10 - tmp11;
z1 = (tmp12 + tmp13) * (double) 0.707106781;
output[i][2] = tmp13 + z1;
output[i][6] = tmp13 - z1;
tmp10 = tmp4 + tmp5;
tmp11 = tmp5 + tmp6;
tmp12 = tmp6 + tmp7;
z5 = (tmp10 - tmp12) * (double) 0.382683433;
z2 = ((double) 0.541196100) * tmp10 + z5;
z4 = ((double) 1.306562965) * tmp12 + z5;
z3 = tmp11 * ((double) 0.707106781);
z11 = tmp7 + z3;
z13 = tmp7 - z3;
output[i][5] = z13 + z2;
output[i][3] = z13 - z2;
output[i][1] = z11 + z4;
output[i][7] = z11 - z4;
}
for (i = 0; i < 8; i++)
{
tmp0 = output[0][i] + output[7][i];
tmp7 = output[0][i] - output[7][i];
tmp1 = output[1][i] + output[6][i];
tmp6 = output[1][i] - output[6][i];
tmp2 = output[2][i] + output[5][i];
tmp5 = output[2][i] - output[5][i];
tmp3 = output[3][i] + output[4][i];
tmp4 = output[3][i] - output[4][i];
tmp10 = tmp0 + tmp3;
tmp13 = tmp0 - tmp3;
tmp11 = tmp1 + tmp2;
tmp12 = tmp1 - tmp2;
output[0][i] = tmp10 + tmp11;
output[4][i] = tmp10 - tmp11;
z1 = (tmp12 + tmp13) * (double) 0.707106781;
output[2][i] = tmp13 + z1;
output[6][i] = tmp13 - z1;
tmp10 = tmp4 + tmp5;
tmp11 = tmp5 + tmp6;
tmp12 = tmp6 + tmp7;
z5 = (tmp10 - tmp12) * (double) 0.382683433;
z2 = ((double) 0.541196100) * tmp10 + z5;
z4 = ((double) 1.306562965) * tmp12 + z5;
z3 = tmp11 * ((double) 0.707106781);
z11 = tmp7 + z3;
z13 = tmp7 - z3;
output[5][i] = z13 + z2;
output[3][i] = z13 - z2;
output[1][i] = z11 + z4;
output[7][i] = z11 - z4;
}
return output;
}
}