/*
* Traverses the original and mask images in tandem.
* The mask should be identical to the original except it
* should have been preselected to be a binary image.
*
* Wherever the mask has a 1 value, add that pixel value to
* the list.
*
* Return the list unsorted and only containing pixel values of
* the original matching a corresponding mask 1-value.
*
* @param orig
* The original ImageData image
* @param mask
* The corresponding ImageData mask (having identical dimensions and containing binary values)
*
*/
public ArrayList mask(ImageData orig, ImageData mask) {
ArrayList list =
new ArrayList(); // a column-wise traversal of the input images populates this 1D list
for (int col = 0; col < orig.getNumCols(); col++) {
for (int row = 0; row < orig.getNumRows(); row++) {
for (int band = 0; band < orig.getNumBands(); band++) {
if (mask.getValue(row, col, band) == 1) {
list.add(new Double(orig.getValue(row, col, band)));
}
}
}
}
return list;
}
/*
* Returns the sum of the pixel values of a given ImageData.
* @param o
* The ImageData providing pixels to be counted
*/
public double sum(ImageData o) {
double sum = 0;
for (int row = 0; row < o.getNumRows(); row++) {
for (int col = 0; col < o.getNumCols(); col++) {
for (int band = 0; band < o.getNumBands(); band++) {
sum += o.getValue(row, col, band);
}
}
}
return sum;
}
public ArrayList vectorize(ImageData o) {
ArrayList list = new ArrayList();
for (int row = 0; row < o.getNumRows(); row++) {
for (int col = 0; col < o.getNumCols(); col++) {
for (int band = 0; band < o.getNumBands(); band++) {
list.add(new Double(o.getValue(row, col, band)));
}
}
}
return list;
}
