机器学习中LPQ特征提取与卷积实现

enum ConvolutionType {
/* Return the full convolution, including border */
CONVOLUTION_FULL,

/* Return only the part that corresponds to the original image */
CONVOLUTION_SAME,
/* Return only the submatrix containing elements that were not influenced by the border */
CONVOLUTION_VALID
};

Mat_<double> conv2(const Mat_<double> img, const Mat_<double> ikernel, ConvolutionType type)
{
Mat_<double> dest;
Mat_<double> kernel;
flip(ikernel, kernel, -1);
Mat_<double> source = img;
if (CONVOLUTION_FULL == type)
{
source = Mat();
const int additionalRows = kernel.rows - 1, additionalCols = kernel.cols - 1;
copyMakeBorder(img, source, (additionalRows + 1) / 2, additionalRows / 2, (additionalCols + 1) / 2, additionalCols / 2, BORDER_CONSTANT, Scalar(0));
}
Point anchor(kernel.cols - kernel.cols / 2 - 1, kernel.rows - kernel.rows / 2 - 1);
int borderMode = BORDER_CONSTANT;
filter2D(source, dest, img.depth(), kernel, anchor, 0, borderMode);

if (CONVOLUTION_VALID == type)
{
dest = dest.colRange((kernel.cols - 1) / 2, dest.cols - kernel.cols / 2).rowRange((kernel.rows - 1) / 2, dest.rows - kernel.rows / 2);
}