Recursive Gaussian derivative filters
نویسندگان
چکیده
We propose a new strategy to design recursive implementations of the Gaussian filter and Gaussian regularized derivative filters. Each recursive filter consists of a cascade of two stable Nth-order subsystems (causal and anti-causal). The computational complexity is 2N multiplications per pixel per dimension independent of the size (σ) of the Gaussian kernel. The filter coefficients have a closed-form solution as a function of scale (σ) and recursion order N (N=3,4,5). The recursive filters yield a high accuracy and excellent isotropy in n-D space.
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