let’s say we have an image (single plane), and a corresponding matrix V. we want to smooth the image using a 2d gaussian kernel at each pixel (i, j). the gaussian kernel is parametrized with the mean that is the pixel value (i, j) of the image and standard deviation that is the corresponding value in the matrix V at the position (i, j).
the image could be single or minibatch.
- is there an efficient way to do this?
- can we use one single filter that re-parametrize itself dynamically with respect to V?