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Algorithms and Hardware for Efficient Image Smoothing by Anup Basu; Christopher M. Brown is a Computer Science article available to read on EtoBox.

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This work develops some algorithms for efficient implementation of mean and separable median filters for image noise smoothing. The procedures suggested use one-dimensional algorithms repeatedly to obtain two-dimensional mean and separable median in < 4 and 4[log2(n + 1)] -2 operations, respectively, for an n X n square neighborhood (nbhd). A simple generalization of the algorithms to k dimensions shows that at most 2k and k(2Jlog 2 (n + 1)] -1) operations are required for obtaining the mean and separable median of an n k nbhd, However, parallel processing can be easily applied to these algorithms. Given only five parallel processors, less than one operation is required to obtain the sum of an n x n nbhd in two dimensions, and for n \_< 31 the maximum number of comparisons required to obtain the two-dimensional separable median filter of an n • n nbhd is reduced to less than four. Experimentally we demonstrate that the separable median filter performs better than the median filter for certain classes of images. A simple hardware implementation of the above algorithm is also outlined. It is seen that the complexity of this implementation increases linearly depending on the number of

Who reads Algorithms and Hardware for Efficient Image Smoothing?

Author

Anup Basu; Christopher M. Brown

Publisher

Elsevier Science; Elsevier ; Academic Press; Elsevier BV (ISSN 0734-189X)

Published

1987

Language

EN

Field

Computer Science (Physical Sciences)