/*
src: input image
kSize: window size used by local average
return: filtered image
*/
Mat Dip2::averageFilter(Mat& src, int kSize){
Mat kernel = Mat(kSize, kSize, CV_32FC1, 1.0/(kSize * kSize));
Mat copy = src.clone();
Mat result = spatialConvolution(copy, kernel);
return result;
}
/*
in input image
size size of filter kernel
spatial true if convolution shall be performed in spatial domain, false otherwise
return smoothed image
*/
Mat Dip3::mySmooth(Mat& in, int size, bool spatial){
// create filter kernel
Mat kernel = createGaussianKernel(size);
// perform convoltion
if (spatial)
return spatialConvolution(in, kernel);
else
return frequencyConvolution(in, kernel);
}
/*
src: input image
kSize: window size used by local average
return: filtered image
*/
Mat Dip2::averageFilter(Mat& src, int kSize){
Mat kernel = Mat::ones( kSize, kSize, src.type());
Mat outputImage = spatialConvolution(src, kernel);
return outputImage / (float)(kSize * kSize);
}
// checks basic properties of the convolution result
void Dip2::test_spatialConvolution(void){
Mat input = Mat::ones(9,9, CV_32FC1);
input.at<float>(4,4) = 255;
Mat kernel = Mat(3,3, CV_32FC1, 1./9.);
Mat output = spatialConvolution(input, kernel);
if ( (input.cols != output.cols) || (input.rows != output.rows) ){
cout << "ERROR: Dip2::spatialConvolution(): input.size != output.size --> Wrong border handling?" << endl;
return;
}
if ( (sum(output.row(0) < 0).val[0] > 0) ||
(sum(output.row(0) > 255).val[0] > 0) ||
(sum(output.row(8) < 0).val[0] > 0) ||
(sum(output.row(8) > 255).val[0] > 0) ||
(sum(output.col(0) < 0).val[0] > 0) ||
(sum(output.col(0) > 255).val[0] > 0) ||
(sum(output.col(8) < 0).val[0] > 0) ||
(sum(output.col(8) > 255).val[0] > 0) ){
cout << "ERROR: Dip2::spatialConvolution(): Border of convolution result contains too large/small values --> Wrong border handling?" << endl;
return;
}else{
if ( (sum(output < 0).val[0] > 0) ||
(sum(output > 255).val[0] > 0) ){
cout << "ERROR: Dip2::spatialConvolution(): Convolution result contains too large/small values!" << endl;
return;
}
}
float ref[9][9] = {{0, 0, 0, 0, 0, 0, 0, 0, 0},
{0, 1, 1, 1, 1, 1, 1, 1, 0},
{0, 1, 1, 1, 1, 1, 1, 1, 0},
{0, 1, 1, (8+255)/9., (8+255)/9., (8+255)/9., 1, 1, 0},
{0, 1, 1, (8+255)/9., (8+255)/9., (8+255)/9., 1, 1, 0},
{0, 1, 1, (8+255)/9., (8+255)/9., (8+255)/9., 1, 1, 0},
{0, 1, 1, 1, 1, 1, 1, 1, 0},
{0, 1, 1, 1, 1, 1, 1, 1, 0},
{0, 0, 0, 0, 0, 0, 0, 0, 0}};
for(int y=1; y<8; y++){
for(int x=1; x<8; x++){
if (abs(output.at<float>(y,x) - ref[y][x]) > 0.0001){
cout << "ERROR: Dip2::spatialConvolution(): Convolution result contains wrong values!" << endl;
return;
}
}
}
input.setTo(0);
input.at<float>(4,4) = 255;
kernel.setTo(0);
kernel.at<float>(0,0) = -1;
output = spatialConvolution(input, kernel);
if ( abs(output.at<float>(5,5) + 255.) < 0.0001 ){
cout << "ERROR: Dip2::spatialConvolution(): Is filter kernel \"flipped\" during convolution? (Check lecture/exercise slides)" << endl;
return;
}
if ( ( abs(output.at<float>(2,2) + 255.) < 0.0001 ) || ( abs(output.at<float>(4,4) + 255.) < 0.0001 ) ){
cout << "ERROR: Dip2::spatialConvolution(): Is anchor point of convolution the centre of the filter kernel? (Check lecture/exercise slides)" << endl;
return;
}
cout << "Message: Dip2::spatialConvolution() seems to be correct" << endl;
}
