Package org.opencv.ximgproc

Class EdgeAwareInterpolator

  • public class EdgeAwareInterpolator
extends SparseMatchInterpolator
    Sparse match interpolation algorithm based on modified locally-weighted affine estimator from CITE: Revaud2015 and Fast Global Smoother as post-processing filter.

    • Constructor Detail

      • EdgeAwareInterpolator

        protected EdgeAwareInterpolator​(long addr)

    • Method Detail

      • 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