void ImageMean<T>::compute(int x, int y, T darkvalue) {
// if the dark value is invalid, then the computed value
// is also invalid
if (darkvalue != darkvalue) {
image->pixel(x, y) = darkvalue;
var->pixel(x, y) = darkvalue;
return;
}
// perform mean (and possibly variance) computation in the
// case where
//T m;
T X = 0, X2 = 0;
typename std::vector<PV>::const_iterator j;
unsigned int counter = 0;
for (j = pvs.begin(); j != pvs.end(); j++) {
T v = j->pixelvalue(x, y);
// skip this value if it is a NaN
if (v != v)
continue;
if (v < darkvalue) {
v = 0;
} else {
v = v - darkvalue;
}
X += v;
if (enableVariance) {
X2 += v * v;
}
counter++;
}
if (counter != pvs.size()) {
debug(LOG_DEBUG, DEBUG_LOG, 0, "bad pixel values at (%d, %d): %d", x, y, counter);
}
T EX = X / counter;
T EX2 = 0;
if (enableVariance) {
EX2 = X2 / counter;
}
// if we don't have the variance, we leave it at that
if (!enableVariance) {
image->pixel(x, y) = EX;
return;
}
// if the variance is enabled, then we can do the computation
// again, and ignore not only the bad values, but also the
// ones that are more then 3 standard deviations away from
// the mean
X = 0, X2 = 0;
counter = 0;
T stddevk = k * sqrt(EX2 - EX * EX);
if (stddevk < 1) {
stddevk = std::numeric_limits<T>::infinity();
}
for (j = pvs.begin(); j != pvs.end(); j++) {
T v = j->pixelvalue(x, y);
// skip NaNs
if (v != v)
continue;
if (v < darkvalue) {
v = 0;
} else {
v = v - darkvalue;
}
// skip values that are too far off
if (fabs(v - EX) > stddevk) {
continue;
}
X += v;
X2 += v * v;
counter++;
}
if (0 == counter) {
image->pixel(x, y) = std::numeric_limits<T>::quiet_NaN();
var->pixel(x, y) = std::numeric_limits<T>::quiet_NaN();
return;
}
EX = X / counter;
EX2 = X2 / counter;
image->pixel(x, y) = EX;
var->pixel(x, y) = EX2 - EX * EX;
}
