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Improved DEM filtering when NaNs present

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This commit is contained in:
Martin Tůma 2024-08-27 22:38:32 +02:00
parent 4b3327fcb1
commit 96a24339c5
1 changed files with 82 additions and 22 deletions
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104
src/map/filter.cpp
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@ -95,35 +95,95 @@ static void gaussBlur4(MatrixD &src, MatrixD &dst, int r)
boxBlur4(src, dst, (bxs.at(2) - 1) / 2); boxBlur4(src, dst, (bxs.at(2) - 1) / 2);
} }
static double avg(const MatrixD &m, int pi, int pj, int r)
{
int col, row, cnt = 0;
double sum = 0;
if (r >= qMax(m.h(), m.w()))
return NAN;
row = pi - r;
if (row >= 0) {
for (int j = qMax(pj - r, 0); j < qMin(pj + r, m.w()); j++) {
if (!std::isnan(m.at(row, j))) {
sum += m.at(row, j);
cnt++;
}
}
}
row = pi + r;
if (row < m.h()) {
for (int j = qMax(pj - r, 0); j < qMin(pj + r, m.w()); j++) {
if (!std::isnan(m.at(row, j))) {
sum += m.at(row, j);
cnt++;
}
}
}
col = pj - r;
if (col >= 0) {
for (int i = qMax(pi - r + 1, 0); i < qMin(pi + r - 1, m.h()); i++) {
if (!std::isnan(m.at(i, col))) {
sum += m.at(i, col);
cnt++;
}
}
}
col = pj + r;
if (col < m.w()) {
for (int i = qMax(pi - r + 1, 0); i < qMin(pi + r - 1, m.h()); i++) {
if (!std::isnan(m.at(i, col))) {
sum += m.at(i, col);
cnt++;
}
}
}
if (cnt)
return sum / cnt;
else
return avg(m, pi, pj, r + 1);
}
static bool fillNANs(const MatrixD &m, MatrixD &src)
{
bool hasNAN = false;
for (int i = 0; i < m.h(); i++) {
for (int j = 0; j < m.w(); j++) {
if (std::isnan(m.at(i, j))) {
hasNAN = true;
double val = avg(src, i, j, 1);
if (std::isnan(val))
return false;
else
src.at(i, j) = val;
}
}
}
return hasNAN;
}
static void revertNANs(const MatrixD &m, MatrixD &dst)
{
for (int i = 0; i < m.size(); i++)
if (std::isnan(m.at(i)))
dst.at(i) = NAN;
}
MatrixD Filter::blur(const MatrixD &m, int radius) MatrixD Filter::blur(const MatrixD &m, int radius)
{ {
MatrixD src(m); MatrixD src(m);
MatrixD dst(m.h(), m.w()); MatrixD dst(m.h(), m.w());
double sum = 0; bool hasNAN = fillNANs(m, src);
int cnt = 0;
for (int i = 0; i < m.size(); i++) {
if (!std::isnan(m.at(i))) {
sum += m.at(i);
cnt++;
}
}
if (cnt != m.size()) {
double avg = sum / cnt;
for (int i = 0; i < m.size(); i++)
if (std::isnan(m.at(i)))
src.at(i) = avg;
}
gaussBlur4(src, dst, radius); gaussBlur4(src, dst, radius);
if (cnt != m.size()) { if (hasNAN)
for (int i = 0; i < dst.size(); i++) revertNANs(m, dst);
if (std::isnan(m.at(i)))
dst.at(i) = NAN;
}
return dst; return dst;
} }