private void printFuncs(AutoTypeImage imageIn, AutoTypeImage imageOut) {
this.imageIn = imageIn;
this.imageOut = imageOut;
if (imageIn.isInteger()) genName = "I32";
else genName = "F" + imageIn.getNumBits();
;
sumType = imageIn.getSumType();
printHorizontal();
printVertical();
printHorizontalInverse();
printVerticalInverse();
}
private void createFile(AutoTypeImage imageType) throws FileNotFoundException {
String suffix = imageType.getAbbreviatedType();
suffix = suffix.compareTo("S32") == 0 ? "I32" : suffix;
className = "Kernel1D_" + suffix;
String sumType = imageType.getSumType();
setOutputFile(className);
out.print(
"/**\n"
+ " * Floating point 1D convolution kernel that extends {@link Kernel1D}.\n"
+ " *\n"
+ " * <p>\n"
+ " * WARNING: Do not modify. Automatically generated by {@link "
+ getClass().getName()
+ "}.\n"
+ " * </p>\n"
+ " *\n"
+ " * @author Peter Abeles\n"
+ " */\n"
+ "public class "
+ className
+ " extends Kernel1D {\n"
+ "\n"
+ "\tpublic "
+ sumType
+ " data[];\n"
+ "\n"
+ "\t/**\n"
+ "\t * Creates a new kernel whose initial values are specified by data and width. The length\n"
+ "\t * of its internal data will be width. Data must be at least as long as width.\n"
+ "\t *\n"
+ "\t * @param data The value of the kernel. Not modified. Reference is not saved.\n"
+ "\t * @param width The kernels width. Must be odd.\n"
+ "\t */\n"
+ "\tpublic "
+ className
+ "("
+ sumType
+ " data[], int width) {\n"
+ "\t\tthis(data,width/2,width);\n"
+ "\t}\n"
+ "\n"
+ "\t/**\n"
+ "\t * Creates a new kernel whose initial values are specified by data and width. The length\n"
+ "\t * of its internal data will be width. Data must be at least as long as width.\n"
+ "\t *\n"
+ "\t * @param data The value of the kernel. Not modified. Reference is not saved.\n"
+ "\t * @param width The kernels width. Must be odd.\n"
+ "\t * @param offset Location of the origin in the array\n"
+ "\t */\n"
+ "\tpublic "
+ className
+ "("
+ sumType
+ " data[], int offset , int width) {\n"
+ "\t\tsuper(offset,width);\n"
+ "\n"
+ "\t\tthis.data = new "
+ sumType
+ "[width];\n"
+ "\t\tSystem.arraycopy(data, 0, this.data, 0, width);\n"
+ "\t}\n"
+ "\n"
+ "\t/**\n"
+ "\t * Create a kernel whose elements are all equal to zero.\n"
+ "\t *\n"
+ "\t * @param width How wide the kernel is. Must be odd.\n"
+ "\t */\n"
+ "\tpublic "
+ className
+ "(int width) {\n"
+ "\t\tthis(width/2,width);\n"
+ "\t}\n"
+ "\n"
+ "\t/**\n"
+ "\t * Create a kernel whose elements are all equal to zero.\n"
+ "\t *\n"
+ "\t * @param width How wide the kernel is. Must be odd.\n"
+ "\t * @param offset Location of the origin in the array\n"
+ "\t */\n"
+ "\tpublic "
+ className
+ "(int offset , int width) {\n"
+ "\t\tsuper(offset,width);\n"
+ "\t\tdata = new "
+ sumType
+ "[width];\n"
+ "\t}\n"
+ "\n"
+ "\tprotected "
+ className
+ "() {\n"
+ "\t}\n"
+ "\n"
+ "\t/**\n"
+ "\t * Creates a kernel whose elements are the specified data array and has\n"
+ "\t * the specified width.\n"
+ "\t *\n"
+ "\t * @param data The array who will be the kernel's data. Reference is saved.\n"
+ "\t * @param width The kernel's width.\n"
+ "\t * @return A new kernel.\n"
+ "\t */\n"
+ "\tpublic static "
+ className
+ " wrap("
+ sumType
+ " data[], int width) {\n"
+ "\t\t"
+ className
+ " ret = new "
+ className
+ "();\n"
+ "\t\tret.data = data;\n"
+ "\t\tret.width = width;\n"
+ "\t\tret.offset = width/2;\n"
+ "\n"
+ "\t\treturn ret;\n"
+ "\t}\n"
+ "\n"
+ "\t@Override\n"
+ "\tpublic boolean isInteger() {\n"
+ "\t\treturn "
+ imageType.isInteger()
+ ";\n"
+ "\t}\n"
+ "\n"
+ "\tpublic "
+ sumType
+ " get(int i) {\n"
+ "\t\treturn data[i];\n"
+ "\t}\n"
+ "\n"
+ "\tpublic "
+ sumType
+ " computeSum() {\n"
+ "\t\t"
+ sumType
+ " sum = 0;\n"
+ "\t\tfor( int i = 0; i < data.length; i++ ) {\n"
+ "\t\t\tsum += data[i];\n"
+ "\t\t}\n"
+ "\n"
+ "\t\treturn sum;\n"
+ "\t}\n"
+ "\n"
+ "\tpublic "
+ sumType
+ "[] getData() {\n"
+ "\t\treturn data;\n"
+ "\t}\n"
+ "\n"
+ "\tpublic void print() {\n"
+ "\t\tfor (int i = 0; i < width; i++) {\n");
if (imageType.isInteger()) out.print("\t\t\tSystem.out.printf(\"%6d \", data[i]);\n");
else if (imageType.isInteger()) out.print("\t\t\tSystem.out.printf(\"%6.3f \", data[i]);\n");
out.print("\t\t}\n" + "\t\tSystem.out.println();\n" + "\t}\n" + "}\n\n");
}
private void printVerticalInverse() {
out.print(
"\t/**\n"
+ "\t * Performs a single level inverse wavelet transform along the vertical axis.\n"
+ "\t *\n"
+ "\t * @param inverseCoef Description of wavelet coefficients.\n"
+ "\t * @param input Transformed image. Not modified.\n"
+ "\t * @param output Reconstruction of original image. Modified\n"
+ "\t */\n"
+ "\tpublic static void verticalInverse( BorderIndex1D border , WlBorderCoef<WlCoef_"
+ genName
+ "> inverseCoef , "
+ imageIn.getSingleBandName()
+ " input , "
+ imageIn.getSingleBandName()
+ " output ) {\n"
+ "\n"
+ "\t\tUtilWavelet.checkShape(output,input);\n"
+ "\n"
+ "\t\t"
+ sumType
+ " []trends = new "
+ sumType
+ "[ output.height ];\n"
+ "\t\t"
+ sumType
+ " []details = new "
+ sumType
+ "[ output.height ];\n"
+ "\n"
+ "\t\tboolean isLarger = input.height > output.height;\n"
+ "\t\tint paddedHeight = output.height + output.height%2;\n"
+ "\n"
+ "\t\tfinal int lowerBorder = inverseCoef.getLowerLength()*2;\n"
+ "\t\tfinal int upperBorder = output.height - inverseCoef.getUpperLength()*2;\n"
+ "\n"
+ "\t\tborder.setLength(output.height+output.height%2);\n"
+ "\n");
if (imageIn.isInteger()) {
out.print("\t\tWlCoef_" + genName + " coefficients = inverseCoef.getInnerCoefficients();\n");
out.print(
"\t\tfinal int e = coefficients.denominatorScaling*2;\n"
+ "\t\tfinal int f = coefficients.denominatorWavelet*2;\n"
+ "\t\tfinal int ef = e*f;\n"
+ "\t\tfinal int ef2 = ef/2;\n");
} else {
out.print("\t\tWlCoef_" + genName + " coefficients;\n");
}
out.print("\n");
out.print(
"\t\tfor( int x = 0; x < output.width; x++) {\n"
+ "\n"
+ "\t\t\tfor( int i = 0; i < details.length; i++ ) {\n"
+ "\t\t\t\tdetails[i] = 0;\n"
+ "\t\t\t\ttrends[i] = 0;\n"
+ "\t\t\t}\n"
+ "\n"
+ "\t\t\tfor( int y = 0; y < output.height; y += 2 ) {\n"
+ "\t\t\t\t"
+ sumType
+ " a = input.get(x,y/2);\n"
+ "\t\t\t\t"
+ sumType
+ " d = input.get(x,y/2+input.height/2);\n"
+ "\n"
+ "\t\t\t\tif( y < lowerBorder ) {\n"
+ "\t\t\t\t\tcoefficients = inverseCoef.getBorderCoefficients(y);\n"
+ "\t\t\t\t} else if( y >= upperBorder ) {\n"
+ "\t\t\t\t\tcoefficients = inverseCoef.getBorderCoefficients(y-paddedHeight);\n"
+ "\t\t\t\t} else {\n"
+ "\t\t\t\t\tcoefficients = inverseCoef.getInnerCoefficients();\n"
+ "\t\t\t\t}\n"
+ "\n"
+ "\t\t\t\tfinal int offsetA = coefficients.offsetScaling;\n"
+ "\t\t\t\tfinal int offsetB = coefficients.offsetWavelet;\n"
+ "\t\t\t\tfinal "
+ sumType
+ "[] alpha = coefficients.scaling;\n"
+ "\t\t\t\tfinal "
+ sumType
+ "[] beta = coefficients.wavelet;\n"
+ "\n"
+ "\t\t\t\t// add the 'average' signal\n"
+ "\t\t\t\tfor( int i = 0; i < alpha.length; i++ ) {\n"
+ "\t\t\t\t\t// if an odd image don't update the outer edge\n"
+ "\t\t\t\t\tint yy = border.getIndex(y+offsetA+i);\n"
+ "\t\t\t\t\tif( isLarger && yy >= output.height )\n"
+ "\t\t\t\t\t\tcontinue;\n"
+ "\t\t\t\t\ttrends[yy] += a*alpha[i];\n"
+ "\t\t\t\t}\n"
+ "\n"
+ "\t\t\t\t// add the detail signal\n"
+ "\t\t\t\tfor( int i = 0; i < beta.length; i++ ) {\n"
+ "\t\t\t\t\tint yy = border.getIndex(y+offsetB+i);\n"
+ "\t\t\t\t\tif( isLarger && yy >= output.height )\n"
+ "\t\t\t\t\t\tcontinue;\n"
+ "\t\t\t\t\tdetails[yy] += d*beta[i];\n"
+ "\t\t\t\t}\n"
+ "\t\t\t}\n"
+ "\n"
+ "\t\t\tfor( int y = 0; y < output.height; y++ ) {\n");
if (imageIn.isInteger()) {
out.print("\t\t\t\toutput.set(x,y, UtilWavelet.round(trends[y]*f + details[y]*e,ef2,ef));\n");
} else {
out.print("\t\t\t\toutput.set(x,y, trends[y] + details[y]);\n");
}
out.print("\t\t\t}\n" + "\t\t}\n" + "\t}\n\n");
}
private void printVertical() {
out.print(
"\t/**\n"
+ "\t * Performs a single level wavelet transform along the vertical axis.\n"
+ "\t *\n"
+ "\t * @param coefficients Description of wavelet coefficients.\n"
+ "\t * @param input Input image which is being transform. Not modified.\n"
+ "\t * @param output where the output is written to. Modified\n"
+ "\t */\n"
+ "\tpublic static void vertical( BorderIndex1D border , WlCoef_"
+ genName
+ " coefficients ,\n"
+ "\t\t\t\t\t\t\t\t "
+ imageIn.getSingleBandName()
+ " input , "
+ imageIn.getSingleBandName()
+ " output ) {\n"
+ "\n"
+ "\t\tUtilWavelet.checkShape(input,output);\n"
+ "\n"
+ "\t\tfinal int offsetA = coefficients.offsetScaling;\n"
+ "\t\tfinal int offsetB = coefficients.offsetWavelet;\n"
+ "\t\tfinal "
+ sumType
+ "[] alpha = coefficients.scaling;\n"
+ "\t\tfinal "
+ sumType
+ "[] beta = coefficients.wavelet;\n"
+ "\n"
+ "\t\tborder.setLength(input.height+input.height%2);\n"
+ "\n"
+ "\t\tboolean isLarger = output.height > input.height;\n"
+ "\n"
+ "\t\tfor( int x = 0; x < input.width; x++) {\n"
+ "\t\t\tfor( int y = 0; y < input.height; y += 2 ) {\n"
+ "\t\t\t\t"
+ sumType
+ " scale = 0;\n"
+ "\t\t\t\t"
+ sumType
+ " wavelet = 0;\n"
+ "\n"
+ "\t\t\t\tfor( int i = 0; i < alpha.length; i++ ) {\n"
+ "\t\t\t\t\tint yy = border.getIndex(y+i+offsetA);\n"
+ "\t\t\t\t\tif( isLarger && yy >= input.height )\n"
+ "\t\t\t\t\t\tcontinue;\n"
+ "\t\t\t\t\tscale += input.get(x,yy)*alpha[i];\n"
+ "\t\t\t\t}\n"
+ "\t\t\t\tfor( int i = 0; i < beta.length; i++ ) {\n"
+ "\t\t\t\t\tint yy = border.getIndex(y+i+offsetB);\n"
+ "\t\t\t\t\tif( isLarger && yy >= input.height )\n"
+ "\t\t\t\t\t\tcontinue;\n"
+ "\t\t\t\t\twavelet += input.get(x,yy)*beta[i];\n"
+ "\t\t\t\t}\n"
+ "\n"
+ "\t\t\t\tint outY = y/2;\n"
+ "\n");
if (imageIn.isInteger()) {
out.print(
"\t\t\t\tscale = 2*scale/coefficients.denominatorScaling;\n"
+ "\t\t\t\twavelet = 2*wavelet/coefficients.denominatorWavelet;\n"
+ "\n");
}
out.print(
"\t\t\t\toutput.set(x , outY,scale);\n"
+ "\t\t\t\toutput.set(x , output.height/2 + outY , wavelet );\n"
+ "\t\t\t}\n"
+ "\t\t}\n"
+ "\t}\n\n");
}
