/**
* Fills the whole image with the specified pixel value
*
* @param img An image.
* @param value The value that the image is being filled with.
*/
public static void fill(ImageSInt64 img, long value) {
final int h = img.getHeight();
final int w = img.getWidth();
long[] data = img.data;
for (int y = 0; y < h; y++) {
int index = img.getStartIndex() + y * img.getStride();
for (int x = 0; x < w; x++) {
data[index++] = value;
}
}
}
/**
* Computes the mean squared error (MSE) between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double computeMeanSquaredError(ImageSInt64 imgA, ImageSInt64 imgB) {
final int h = imgA.getHeight();
final int w = imgA.getWidth();
double total = 0;
for (int y = 0; y < h; y++) {
for (int x = 0; x < w; x++) {
double difference = imgA.get(x, y) - imgB.get(x, y);
total += difference * difference;
}
}
return total / (w * h);
}
/**
* Sets each value in the image to a value drawn from an uniform distribution that has a range of
* min <= X < max.
*/
public static void randomize(ImageSInt64 img, Random rand, long min, long max) {
final int h = img.getHeight();
final int w = img.getWidth();
long range = max - min;
long[] data = img.data;
for (int y = 0; y < h; y++) {
int index = img.getStartIndex() + y * img.getStride();
for (int x = 0; x < w; x++) {
data[index++] = rand.nextInt((int) range) + min;
}
}
}
/** Adds Gaussian/normal i.i.d noise to each pixel in the image. */
public static void addGaussian(ImageSInt64 img, Random rand, double sigma, long min, long max) {
final int h = img.getHeight();
final int w = img.getWidth();
long[] data = img.data;
for (int y = 0; y < h; y++) {
int index = img.getStartIndex() + y * img.getStride();
for (int x = 0; x < w; x++) {
long value = (data[index]) + (long) (rand.nextGaussian() * sigma);
if (value < min) value = min;
if (value > max) value = max;
data[index++] = value;
}
}
}