filters
¶skfuzzy.filters.fire1d (x[, l1, l2]) |
1-D filtering using Fuzzy Inference Ruled by Else-action (FIRE) [1]. |
skfuzzy.filters.fire2d (im[, l1, l2, ...]) |
2-D filtering using Fuzzy Inference Ruled by Else-action (FIRE) [1]. |
skfuzzy.filters.
fire1d
(x, l1=0, l2=1)[source]¶1-D filtering using Fuzzy Inference Ruled by Else-action (FIRE) [1].
FIRE filtering is nonlinear, and is specifically designed to remove impulse (salt and pepper) noise.
Parameters: | x : 1d array or iterable
l1 : float
l2 : float
|
---|---|
Returns: | y : 1d array
|
Notes
Filtering occurs for l1 < |x| < l2
; for |x| < l1
there is no
effect.
References
[R29] | Fabrizio Russo, Fuzzy Filtering of Noisy Sensor Data, IEEE Instrumentation and Measurement Technology Conference, Brussels, Belgium, June 4 - 6, 1996, pp 1281 - 1285. |
skfuzzy.filters.
fire2d
(im, l1=0, l2=255, fuzzyresolution=1)[source]¶2-D filtering using Fuzzy Inference Ruled by Else-action (FIRE) [1].
FIRE filtering is nonlinear, and is specifically designed to remove impulse (salt and pepper) noise.
Parameters: | I : 2d array
l1 : float
l2 : float
fuzzyresolution : float, default = 1
|
---|---|
Returns: | J : 2d array
|
Notes
Filtering occurs for l1 < |x| < l2
; outside this range the data is
unaffected.
References
[R30] | Fabrizio Russo, Fuzzy Filtering of Noisy Sensor Data, IEEE Instrumentation and Measurement Technology Conference, Brussels, Belgium, June 4 - 6, 1996, pp 1281 - 1285. |