private void histogramMatching(String inputHeader1, String inputHeader2, String outputHeader) {
// check to see that the inputHeader and outputHeader are not null.
if (inputHeader1.isEmpty() || outputHeader.isEmpty() || inputHeader2.isEmpty()) {
showFeedback("One or more of the input parameters have not been set properly.");
return;
}
try {
int row, col;
double z;
int progress = 0;
int numCells1 = 0;
int numCells2 = 0;
int i = 0;
WhiteboxRasterInfo inputFile1 = new WhiteboxRasterInfo(inputHeader1);
int rows1 = inputFile1.getNumberRows();
int cols1 = inputFile1.getNumberColumns();
double noData1 = inputFile1.getNoDataValue();
WhiteboxRasterInfo inputFile2 = new WhiteboxRasterInfo(inputHeader2);
int rows2 = inputFile2.getNumberRows();
int cols2 = inputFile2.getNumberColumns();
double noData2 = inputFile2.getNoDataValue();
WhiteboxRaster outputFile =
new WhiteboxRaster(
outputHeader, "rw", inputHeader1, WhiteboxRaster.DataType.FLOAT, noData1);
outputFile.setPreferredPalette(inputFile1.getPreferredPalette());
double minValue1 = inputFile1.getMinimumValue();
double maxValue1 = inputFile1.getMaximumValue();
int numBins1 =
Math.max(
2 * (int) Math.ceil(maxValue1 - minValue1 + 1),
(int) Math.ceil(Math.pow(rows1 * cols1, 1.0 / 3)));
double binSize = (maxValue1 - minValue1) / numBins1;
long[] histogram = new long[numBins1];
int binNum;
int numBinsLessOne1 = numBins1 - 1;
double[] data;
updateProgress("Histogram matching: ", 0);
for (row = 0; row < rows1; row++) {
data = inputFile1.getRowValues(row);
for (col = 0; col < cols1; col++) {
z = data[col];
if (z != noData1) {
numCells1++;
binNum = (int) ((z - minValue1) / binSize);
if (binNum > numBinsLessOne1) {
binNum = numBinsLessOne1;
}
histogram[binNum]++;
}
}
if (cancelOp) {
cancelOperation();
return;
}
progress = (int) (100f * row / (rows1 - 1));
updateProgress("Histogram matching: ", progress);
}
updateProgress("Histogram matching: ", 0);
double[] cdf = new double[numBins1];
cdf[0] = histogram[0];
for (i = 1; i < numBins1; i++) {
cdf[i] = cdf[i - 1] + histogram[i];
}
for (i = 0; i < numBins1; i++) {
cdf[i] = cdf[i] / numCells1;
}
double minValue2 = inputFile2.getMinimumValue();
double maxValue2 = inputFile2.getMaximumValue();
int numBins2 =
Math.max(
2 * (int) Math.ceil(maxValue2 - minValue2 + 1),
(int) Math.ceil(Math.pow(rows2 * cols2, 1.0 / 3)));
int numBinsLessOne2 = numBins2 - 1;
long[] histogram2 = new long[numBins2];
double[][] referenceCDF = new double[numBins2][2];
for (row = 0; row < rows2; row++) {
data = inputFile2.getRowValues(row);
for (col = 0; col < cols2; col++) {
z = data[col];
if (z != noData2) {
numCells2++;
binNum = (int) ((z - minValue2) / binSize);
if (binNum > numBinsLessOne2) {
binNum = numBinsLessOne2;
}
histogram2[binNum]++;
}
}
if (cancelOp) {
cancelOperation();
return;
}
progress = (int) (100f * row / (rows1 - 1));
updateProgress("Histogram matching: ", progress);
}
// convert the reference histogram to a cdf.
referenceCDF[0][1] = histogram2[0];
for (i = 1; i < numBins2; i++) {
referenceCDF[i][1] = referenceCDF[i - 1][1] + histogram2[i];
}
for (i = 0; i < numBins2; i++) {
referenceCDF[i][0] = minValue2 + (i / (float) numBins2) * (maxValue2 - minValue2);
referenceCDF[i][1] = referenceCDF[i][1] / numCells2;
}
int[] startingVals = new int[11];
double pVal = 0;
for (i = 0; i < numBins2; i++) {
pVal = referenceCDF[i][1];
if (pVal < 0.1) {
startingVals[1] = i;
}
if (pVal < 0.2) {
startingVals[2] = i;
}
if (pVal < 0.3) {
startingVals[3] = i;
}
if (pVal < 0.4) {
startingVals[4] = i;
}
if (pVal < 0.5) {
startingVals[5] = i;
}
if (pVal < 0.6) {
startingVals[6] = i;
}
if (pVal < 0.7) {
startingVals[7] = i;
}
if (pVal < 0.8) {
startingVals[8] = i;
}
if (pVal < 0.9) {
startingVals[9] = i;
}
if (pVal <= 1) {
startingVals[10] = i;
}
}
updateProgress("Histogram matching: ", 0);
int j = 0;
double xVal = 0;
double x1, x2, p1, p2;
for (row = 0; row < rows1; row++) {
data = inputFile1.getRowValues(row);
for (col = 0; col < cols1; col++) {
z = data[col];
if (z != noData1) {
binNum = (int) ((z - minValue1) / binSize);
if (binNum > numBinsLessOne1) {
binNum = numBinsLessOne1;
}
pVal = cdf[binNum];
j = (int) (Math.floor(pVal * 10));
for (i = startingVals[j]; i < numBins2; i++) {
if (referenceCDF[i][1] > pVal) {
if (i > 0) {
x1 = referenceCDF[i - 1][0];
x2 = referenceCDF[i][0];
p1 = referenceCDF[i - 1][1];
p2 = referenceCDF[i][1];
if (p1 != p2) {
xVal = x1 + ((x2 - x1) * ((pVal - p1) / (p2 - p1)));
} else {
xVal = x1;
}
} else {
xVal = referenceCDF[i][0];
}
break;
}
}
outputFile.setValue(row, col, xVal);
}
}
if (cancelOp) {
cancelOperation();
return;
}
progress = (int) (100f * row / (rows1 - 1));
updateProgress("Histogram matching: ", progress);
}
inputFile1.close();
outputFile.close();
} catch (OutOfMemoryError oe) {
myHost.showFeedback("An out-of-memory error has occurred during operation.");
} catch (Exception e) {
myHost.showFeedback("An error has occurred during operation. See log file for details.");
myHost.logException("Error in " + getDescriptiveName(), e);
} finally {
updateProgress("Progress: ", 0);
}
}
/** Used to execute this plugin tool. */
@Override
public void run() {
/*
* This transformation has been taken from:
* http://ij.ms3d.de/pdf/ihs_transforms.pdf
* in reference to Haydn, Dalke, and Henkel (1982)
* Note: 0 <= I <= 3, 0 <= H <= 3, 0 <= S <= 1
*/
amIActive = true;
String redHeader, greenHeader, blueHeader, intensityHeader, saturationHeader, hueHeader;
if (args.length <= 0) {
showFeedback("Plugin parameters have not been set.");
return;
}
redHeader = args[0];
greenHeader = args[1];
blueHeader = args[2];
intensityHeader = args[3];
hueHeader = args[4];
saturationHeader = args[5];
// check to see that the inputHeader and outputHeader are not null.
if (redHeader.isEmpty()
|| greenHeader.isEmpty()
|| blueHeader == null
|| intensityHeader.isEmpty()
|| hueHeader.isEmpty()
|| saturationHeader.isEmpty()) {
showFeedback("One or more of the input parameters have not been set properly.");
return;
}
try {
int row, col;
double redVal, greenVal, blueVal;
// double redRange, greenRange, blueRange;
// double redMin, greenMin, blueMin;
double r, g, b;
double i, s, h, m;
float progress;
WhiteboxRasterInfo red = new WhiteboxRasterInfo(redHeader);
int rows = red.getNumberRows();
int cols = red.getNumberColumns();
WhiteboxRasterInfo green = new WhiteboxRasterInfo(greenHeader);
if (green.getNumberRows() != rows || green.getNumberColumns() != cols) {
showFeedback("All input images must have the same dimensions.");
return;
}
WhiteboxRasterInfo blue = new WhiteboxRasterInfo(blueHeader);
if (blue.getNumberRows() != rows || blue.getNumberColumns() != cols) {
showFeedback("All input images must have the same dimensions.");
return;
}
double redNoData = red.getNoDataValue();
double greenNoData = green.getNoDataValue();
double blueNoData = blue.getNoDataValue();
WhiteboxRaster intensity =
new WhiteboxRaster(
intensityHeader, "rw", redHeader, WhiteboxRaster.DataType.FLOAT, redNoData);
WhiteboxRaster hue =
new WhiteboxRaster(hueHeader, "rw", redHeader, WhiteboxRaster.DataType.FLOAT, redNoData);
WhiteboxRaster saturation =
new WhiteboxRaster(
saturationHeader, "rw", redHeader, WhiteboxRaster.DataType.FLOAT, redNoData);
// redMin = red.getDisplayMinimum();
// greenMin = green.getDisplayMinimum();
// blueMin = blue.getDisplayMinimum();
//
// redRange = red.getDisplayMaximum() - redMin;
// greenRange = green.getDisplayMaximum() - greenMin;
// blueRange = blue.getDisplayMaximum() - blueMin;
double overallMin =
Math.min(
Math.min(red.getDisplayMinimum(), green.getDisplayMinimum()),
blue.getDisplayMinimum());
double overallMax =
Math.max(
Math.max(red.getDisplayMaximum(), green.getDisplayMaximum()),
blue.getDisplayMaximum());
double range = overallMax - overallMin;
double[] dataRed, dataGreen, dataBlue;
for (row = 0; row < rows; row++) {
dataRed = red.getRowValues(row);
dataGreen = green.getRowValues(row);
dataBlue = blue.getRowValues(row);
for (col = 0; col < cols; col++) {
redVal = dataRed[col];
greenVal = dataGreen[col];
blueVal = dataBlue[col];
if ((redVal != redNoData) && (greenVal != greenNoData) && (blueVal != blueNoData)) {
r = (redVal - overallMin) / range;
if (r < 0) {
r = 0;
}
if (r > 1) {
r = 1;
}
g = (greenVal - overallMin) / range;
if (g < 0) {
g = 0;
}
if (g > 1) {
g = 1;
}
b = (blueVal - overallMin) / range;
if (b < 0) {
b = 0;
}
if (b > 1) {
b = 1;
}
m = Math.min(Math.min(r, g), b);
i = r + g + b;
if (i == 3) {
h = 0;
} else if (m == b) {
h = (g - b) / (i - 3 * b);
} else if (m == r) {
h = (b - r) / (i - 3 * r) + 1;
} else { // m == g
h = (r - g) / (i - 3 * g) + 2;
}
if (h <= 1) {
s = (i - 3 * b) / i;
} else if (h <= 2) {
s = (i - 3 * r) / i;
} else { // H <= 3
s = (i - 3 * g) / i;
}
intensity.setValue(row, col, i);
hue.setValue(row, col, h);
saturation.setValue(row, col, s);
} else {
intensity.setValue(row, col, redNoData);
hue.setValue(row, col, redNoData);
saturation.setValue(row, col, redNoData);
}
}
if (cancelOp) {
cancelOperation();
return;
}
progress = (float) (100f * row / (rows - 1));
updateProgress((int) progress);
}
intensity.addMetadataEntry("Created by the " + getDescriptiveName() + " tool.");
intensity.addMetadataEntry("Created on " + new Date());
intensity.close();
hue.addMetadataEntry("Created by the " + getDescriptiveName() + " tool.");
hue.addMetadataEntry("Created on " + new Date());
hue.close();
saturation.addMetadataEntry("Created by the " + getDescriptiveName() + " tool.");
saturation.addMetadataEntry("Created on " + new Date());
saturation.close();
red.close();
green.close();
blue.close();
// returning a header file string displays the image.
returnData(intensityHeader);
returnData(hueHeader);
returnData(saturationHeader);
} catch (OutOfMemoryError oe) {
myHost.showFeedback("An out-of-memory error has occurred during operation.");
} catch (Exception e) {
myHost.showFeedback("An error has occurred during operation. See log file for details.");
myHost.logException("Error in " + getDescriptiveName(), e);
} finally {
updateProgress("Progress: ", 0);
// tells the main application that this process is completed.
amIActive = false;
myHost.pluginComplete();
}
}
