各向异性扩散PM模型原理与C++实现

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本文介绍了各向异性扩散PM模型，并给出了C++代码实现。

一、PM模型原理

其中，

二、C++代码实现

MATLAB代码可参考：http://www.csse.uwa.edu.au/~pk/research/matlabfns/Spatial/anisodiff.m

http://www.mathworks.com/matlabcentral/fileexchange/14995-anisotropic-diffusion-perona-malik/content/anisodiff_Perona-Malik/anisodiff2D.m

void CImageObj::Perona_Malik(int iter, double dt, double kappa, int option){int i, j;int nx = m_width, ny = m_height;double** I_t = NewDoubleMatrix(nx, ny);double** I_tmp = NewDoubleMatrix(nx, ny);for (i = 0; i < ny; i++)for (j = 0; j < nx; j++)I_t[i][j] = I_tmp[i][j] = m_imgData[i][j];for (int t = 0; t < iter; t++){for (i = 0; i < ny; i++){for (j = 0; j < nx; j++){int iUp = i - 1, iDown = i + 1;int jLeft = j - 1, jRight = j + 1;    // 边界处理if (0 == i) iUp = i; if (ny - 1 == i) iDown = i;if (0 == j) jLeft = j; if (nx - 1 == j) jRight = j;double deltaN = I_t[iUp][j] - I_t[i][j];double deltaS = I_t[iDown][j] - I_t[i][j];double deltaE = I_t[i][jRight] - I_t[i][j];double deltaW = I_t[i][jLeft] - I_t[i][j];double cN, cS, cE, cW;if (1 == option){cN = exp(-(deltaN / kappa) * (deltaN / kappa));cS = exp(-(deltaS / kappa) * (deltaS / kappa));cE = exp(-(deltaE / kappa) * (deltaE / kappa));cW = exp(-(deltaW / kappa) * (deltaW / kappa));}else if (2 == option){cN = 1.0 / (1 + (deltaN / kappa) * (deltaN / kappa));cS = 1.0 / (1 + (deltaS / kappa) * (deltaS / kappa));cE = 1.0 / (1 + (deltaE / kappa) * (deltaE / kappa));cW = 1.0 / (1 + (deltaW / kappa) * (deltaW / kappa));}I_tmp[i][j] += dt * (cN * deltaN + cS * deltaS + cE * deltaE + cW * deltaW);}}  // 一次迭代for (i = 0; i < ny; i++)for (j = 0; j < nx; j++){I_t[i][j] = I_tmp[i][j];}} // 迭代结束// 给图像赋值for (i = 0; i < ny; i++)for (j = 0; j < nx; j++){double tmp = I_t[i][j];tmp = max(0, min(tmp, 255));m_imgData[i][j] = (unsigned char)tmp;}DeleteDoubleMatrix(I_t, nx, ny);DeleteDoubleMatrix(I_tmp, nx, ny);}

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