Some articles on sampled gaussian kernel, gaussian kernel, sampled, gaussian:
Scale Space Implementation - The Sampled Gaussian Kernel
... step in practice, the presumably simplest approach is to convolve the discrete signal with a sampled Gaussian kernel where (with ) which in turn is truncated at the ends to give a filter with finite ... a constant C times the standard deviation of the Gaussian kernel where C is often chosen somewhere between 3 and 6 ... Using the sampled Gaussian kernel can, however, lead to implementation problems, in particular when computing higher-order derivatives at finer scales by applying sampled derivatives of Gaussian ...
... step in practice, the presumably simplest approach is to convolve the discrete signal with a sampled Gaussian kernel where (with ) which in turn is truncated at the ends to give a filter with finite ... a constant C times the standard deviation of the Gaussian kernel where C is often chosen somewhere between 3 and 6 ... Using the sampled Gaussian kernel can, however, lead to implementation problems, in particular when computing higher-order derivatives at finer scales by applying sampled derivatives of Gaussian ...
Famous quotes containing the word kernel:
“After night’s thunder far away had rolled
The fiery day had a kernel sweet of cold”
—Edward Thomas (1878–1917)
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