Need Python coding for converting 2D to 3D

Description is as attached 1-LaplaceFocus Measure: In order to detect regions of higher contrast the Laplace operator can be applied. Using the standard Laplace operator yields no response of the filter when fxx =-fyy . The squared second derivation should be used instead of this. For the discreet model the self convolution of the Sobel Operator is applied. In order to increase the robustness the summation of the responses of the two filter masks (horizontal and vertical) in a local window is calculated as the Laplace focus measure F ML. Notice please here it is on 2D and I need it on 3D So this formel misses the z-komponent. 2-Mean Method Focus Measure: If the image is becoming sharper the variance Of the grey values Of that Scene is getting higher. The ratio of the mean grey value to the center grey value in the neighborhood can be taken as new focus measure FM’. The ratio results in one if there is a constant grey value or there is no texture present. If high variations are present the ratio is different from one. This factor needs to be inverted if it is found in the interval (0,1). Like the Laplace measure this focus measure FMm is summed in a local window. Notice please here it is also on 2D and I need it on 3D So these two formel misses the z-komponent. 3-CurvatureFocus Measure: As already discussed in the last section a sharper image region implies a higher grey value variance. Therefore if the grey values are treated as a 3D surface (x,y, g(x,y)), the curvature in a sharp image region is expected to be higher than in an unsharp region. The first step of calculating this curvature based focus measure is to approximate the surface. The coefficients are found using a least squares approximation with g0 and g2 . The next step is to combine these coefficients in order to obtain a sufficient focus measure. Notice please here it is also on 2D and I need it on 3D So here these formel also misses the z-komponent.