Practical Image Processing
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Practical Image Processing for (i=0; i
Transcript of Practical Image Processing
Practical Image Processing
Chap 3Area processing convolution (mask) operation weighted sum of
pixels in a neighborhood of source pixel (convolution window) :
convolution window * convoltion mask ) convolution mask Practical
Image Processing Practical Image Processing
for (i=0; i max) max = diff; diff = abs(ptrSorce[j][i]-
ptrSorce[j][i]);if (diff > max) max = diff; diff =
abs(ptrSorce[j][i+1]- ptrSorce[j][i]);if (diff > max) max =
diff; diff = abs(ptrSorce[j+1][i-1]- ptrSorce[j][i]); if (diff >
max) max = diff; diff = abs(ptrSorce[j+1][i]- ptrSorce[j][i]);if
(diff > max) max = diff; diff = abs(ptrSorce[j+1][i+1]-
ptrSorce[j][i]);if (diff > max) max = diff; ptrDest[j][i] = max;
} Practical Image Processing Practical Image Processing
Difference operator (fig c) subtract surrounding pixels from their
opposing counterparts and choose the maximum Practical Image
Processing Practical Image Processing
void CImageFiltering::Edge_difference() { int i, j, max; CPixelPtr
ptrSorce(m_pImage->GetUndoHandle()); CPixelPtr
ptrDest(*m_pImage); CPixel p; for(j=1 ; j max) max = diff; diff =
abs(ptrSorce[j-1][i+1]- ptrSorce[j+1][i-1]);if (diff > max) max
= diff; diff = abs(ptrSorce[j][i+1]- ptrSorce[j][i-1]); if (diff
> max) max = diff;; ptrDest[j][i] = max; } Practical Image
Processing Practical Image Processing
thresholding an edge map (fig. 3.15) may use single threshold or
double threshold single threshold g(x) = 255 if x >= threshold 0
otherwise double threshold g(x) = 255 if x >= high_threshold 0
if x GetUndoHandle()); CPixelPtr ptrDest_Mag(*m_pImage); CPixelPtr
ptrDest_Phase(*m_pImage); CPixel p; for(j=1 ; j
