[−][src]Trait opencv::prelude::AdaptiveManifoldFilter

pub trait AdaptiveManifoldFilter: AlgorithmTrait {
    pub fn as_raw_AdaptiveManifoldFilter(&self) -> *const c_void;

    pub fn as_raw_mut_AdaptiveManifoldFilter(&mut self) -> *mut c_void;

    pub fn filter(
        &mut self, 
        src: &dyn ToInputArray, 
        dst: &mut dyn ToOutputArray, 
        joint: &dyn ToInputArray
    ) -> Result<()> { ... }

    pub fn collect_garbage(&mut self) -> Result<()> { ... }

    pub fn get_sigma_s(&self) -> Result<f64> { ... }

    pub fn set_sigma_s(&mut self, val: f64) -> Result<()> { ... }

    pub fn get_sigma_r(&self) -> Result<f64> { ... }

    pub fn set_sigma_r(&mut self, val: f64) -> Result<()> { ... }

    pub fn get_tree_height(&self) -> Result<i32> { ... }

    pub fn set_tree_height(&mut self, val: i32) -> Result<()> { ... }

    pub fn get_pca_iterations(&self) -> Result<i32> { ... }

    pub fn set_pca_iterations(&mut self, val: i32) -> Result<()> { ... }

    pub fn get_adjust_outliers(&self) -> Result<bool> { ... }

    pub fn set_adjust_outliers(&mut self, val: bool) -> Result<()> { ... }

    pub fn get_use_rng(&self) -> Result<bool> { ... }

    pub fn set_use_rng(&mut self, val: bool) -> Result<()> { ... }
}

Interface for Adaptive Manifold Filter realizations.

For more details about this filter see Gastal12 and References_.

Below listed optional parameters which may be set up with Algorithm::set function.

  • member double sigma_s = 16.0 Spatial standard deviation.
  • member double sigma_r = 0.2 Color space standard deviation.
  • member int tree_height = -1 Height of the manifold tree (default = -1 : automatically computed).
  • member int num_pca_iterations = 1 Number of iterations to computed the eigenvector.
  • member bool adjust_outliers = false Specify adjust outliers using Eq. 9 or not.
  • member bool use_RNG = true Specify use random number generator to compute eigenvector or not.

Required methods

pub fn as_raw_AdaptiveManifoldFilter(&self) -> *const c_void[src]

pub fn as_raw_mut_AdaptiveManifoldFilter(&mut self) -> *mut c_void[src]

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Provided methods

pub fn filter(
    &mut self,
    src: &dyn ToInputArray,
    dst: &mut dyn ToOutputArray,
    joint: &dyn ToInputArray
) -> Result<()>[src]

Apply high-dimensional filtering using adaptive manifolds.

Parameters

  • src: filtering image with any numbers of channels.

  • dst: output image.

  • joint: optional joint (also called as guided) image with any numbers of channels.

C++ default parameters

  • joint: noArray()

pub fn collect_garbage(&mut self) -> Result<()>[src]

pub fn get_sigma_s(&self) -> Result<f64>[src]

See also

setSigmaS

pub fn set_sigma_s(&mut self, val: f64) -> Result<()>[src]

See also

setSigmaS getSigmaS

pub fn get_sigma_r(&self) -> Result<f64>[src]

See also

setSigmaR

pub fn set_sigma_r(&mut self, val: f64) -> Result<()>[src]

See also

setSigmaR getSigmaR

pub fn get_tree_height(&self) -> Result<i32>[src]

See also

setTreeHeight

pub fn set_tree_height(&mut self, val: i32) -> Result<()>[src]

See also

setTreeHeight getTreeHeight

pub fn get_pca_iterations(&self) -> Result<i32>[src]

See also

setPCAIterations

pub fn set_pca_iterations(&mut self, val: i32) -> Result<()>[src]

See also

setPCAIterations getPCAIterations

pub fn get_adjust_outliers(&self) -> Result<bool>[src]

See also

setAdjustOutliers

pub fn set_adjust_outliers(&mut self, val: bool) -> Result<()>[src]

See also

setAdjustOutliers getAdjustOutliers

pub fn get_use_rng(&self) -> Result<bool>[src]

See also

setUseRNG

pub fn set_use_rng(&mut self, val: bool) -> Result<()>[src]

See also

setUseRNG getUseRNG

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Implementations

impl<'_> dyn AdaptiveManifoldFilter + '_[src]

pub fn create() -> Result<Ptr<dyn AdaptiveManifoldFilter>>[src]

Implementors

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