Constructor Detail

• EdgeAwareInterpolator

  protected EdgeAwareInterpolator​(long addr)

Method Detail

• __fromPtr__

  public static EdgeAwareInterpolator __fromPtr__​(long addr)

• getUsePostProcessing

  public boolean getUsePostProcessing()

  SEE: setUsePostProcessing

  Returns:

  automatically generated

• getFGSLambda

  public float getFGSLambda()

  SEE: setFGSLambda

  Returns:

  automatically generated

• getFGSSigma

  public float getFGSSigma()

  SEE: setFGSLambda

  Returns:

  automatically generated

• getLambda

  public float getLambda()

  SEE: setLambda

  Returns:

  automatically generated

• getSigma

  public float getSigma()

  SEE: setSigma

  Returns:

  automatically generated

• getK

  public int getK()

  SEE: setK

  Returns:

  automatically generated

• setCostMap

  public void setCostMap​(Mat _costMap)

  Interface to provide a more elaborated cost map, i.e. edge map, for the edge-aware term. This implementation is based on a rather simple gradient-based edge map estimation. To used more complex edge map estimator (e.g. StructuredEdgeDetection that has been used in the original publication) that may lead to improved accuracies, the internal edge map estimation can be bypassed here.

  Parameters:

  _costMap - a type CV_32FC1 Mat is required. SEE: cv::ximgproc::createSuperpixelSLIC

• setFGSLambda

  public void setFGSLambda​(float _lambda)

  Sets the respective fastGlobalSmootherFilter() parameter.

  Parameters:

  _lambda - automatically generated

• setFGSSigma

  public void setFGSSigma​(float _sigma)

  SEE: setFGSLambda

  Parameters:

  _sigma - automatically generated

• setK

  public void setK​(int _k)

  K is a number of nearest-neighbor matches considered, when fitting a locally affine model. Usually it should be around 128. However, lower values would make the interpolation noticeably faster.

  Parameters:

  _k - automatically generated

• setLambda

  public void setLambda​(float _lambda)

  Lambda is a parameter defining the weight of the edge-aware term in geodesic distance, should be in the range of 0 to 1000.

  Parameters:

  _lambda - automatically generated

• setSigma

  public void setSigma​(float _sigma)

  Sigma is a parameter defining how fast the weights decrease in the locally-weighted affine fitting. Higher values can help preserve fine details, lower values can help to get rid of noise in the output flow.

  Parameters:

  _sigma - automatically generated

• setUsePostProcessing

  public void setUsePostProcessing​(boolean _use_post_proc)

  Sets whether the fastGlobalSmootherFilter() post-processing is employed. It is turned on by default.

  Parameters:

  _use_post_proc - automatically generated

• finalize

  protected void finalize()
                   throws java.lang.Throwable

  Overrides:

  finalize in class SparseMatchInterpolator

  Throws:

  java.lang.Throwable