Box filter: Difference between revisions
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===Description=== | ===Description=== | ||
BOX_FILTER is a spatial filter that filters and despises based on a moving window (or box). It tends to be slow compared to filter methods that can be vectorized. | |||
====Inputs==== | ====Inputs==== | ||
* '''x''' = | * '''x''' = MxNxP data class 'double' or 'dataset'. If 'dataset' it must x.type=='image' (see BUILDIMAGE). If 'double' it must be MxNxP (P can = 1 or N-way arrays). | ||
* '''win''' = a 1 or 2 element vector of odd integers corresponding to the window width of the box filter. If scalar, (win) is set to win = [win win]. | * '''win''' = a 1 or 2 element vector of odd integers corresponding to the window width of the box filter. If scalar, (win) is set to win = [win win]. | ||
====Outputs==== | ====Outputs==== | ||
* '''xf''' = Filtered image class 'dataset'. | * '''xf''' = Filtered image class 'dataset' or matrix (or N-way array) class 'double.' | ||
===Options=== | ===Options=== |
Revision as of 15:25, 10 September 2018
Purpose
Image or matrix (N-way) filtering (spatial filtering with a moving window)
Synopsis
- xf = box_filter(x,win,options)
Description
BOX_FILTER is a spatial filter that filters and despises based on a moving window (or box). It tends to be slow compared to filter methods that can be vectorized.
Inputs
- x = MxNxP data class 'double' or 'dataset'. If 'dataset' it must x.type=='image' (see BUILDIMAGE). If 'double' it must be MxNxP (P can = 1 or N-way arrays).
- win = a 1 or 2 element vector of odd integers corresponding to the window width of the box filter. If scalar, (win) is set to win = [win win].
Outputs
- xf = Filtered image class 'dataset' or matrix (or N-way array) class 'double.'
Options
options = a structure array with the following fields:
- algorithm: [ {'mean'} | 'median' | 'max' | 'min' | 'meantrimmed' | 'mediantrimmed' ] governs filter method.
- ntrim: when algorithm = 'meantrimmed' or 'mediantrimmed', (ntrim) is the input (n) to the functions MEANTRIMMED or MEDIANTRIMED {default = 2}.