Disparity map filter based on Weighted Least Squares filter (in form of Fast Global Smoother that is a lot faster than traditional Weighted Least Squares filter implementations) and optional use of left-right-consistency-based confidence to refine the results in half-occlusions and uniform areas.
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#include <opencv2/ximgproc/disparity_filter.hpp>
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virtual Mat | getConfidenceMap ()=0 |
| Get the confidence map that was used in the last filter call. It is a CV_32F one-channel image with values ranging from 0.0 (totally untrusted regions of the raw disparity map) to 255.0 (regions containing correct disparity values with a high degree of confidence).
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virtual int | getDepthDiscontinuityRadius ()=0 |
| DepthDiscontinuityRadius is a parameter used in confidence computation. It defines the size of low-confidence regions around depth discontinuities.
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virtual double | getLambda ()=0 |
| Lambda is a parameter defining the amount of regularization during filtering. Larger values force filtered disparity map edges to adhere more to source image edges. Typical value is 8000.
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virtual int | getLRCthresh ()=0 |
| LRCthresh is a threshold of disparity difference used in left-right-consistency check during confidence map computation. The default value of 24 (1.5 pixels) is virtually always good enough.
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virtual Rect | getROI ()=0 |
| Get the ROI used in the last filter call.
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virtual double | getSigmaColor ()=0 |
| SigmaColor is a parameter defining how sensitive the filtering process is to source image edges. Large values can lead to disparity leakage through low-contrast edges. Small values can make the filter too sensitive to noise and textures in the source image. Typical values range from 0.8 to 2.0.
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virtual void | setDepthDiscontinuityRadius (int _disc_radius)=0 |
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virtual void | setLambda (double _lambda)=0 |
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virtual void | setLRCthresh (int _LRC_thresh)=0 |
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virtual void | setSigmaColor (double _sigma_color)=0 |
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virtual void | filter (InputArray disparity_map_left, InputArray left_view, OutputArray filtered_disparity_map, InputArray disparity_map_right=Mat(), Rect ROI=Rect(), InputArray right_view=Mat())=0 |
| Apply filtering to the disparity map.
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| Algorithm () |
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virtual | ~Algorithm () |
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virtual void | clear () |
| Clears the algorithm state.
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virtual bool | empty () const |
| Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.
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virtual String | getDefaultName () const |
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virtual void | read (const FileNode &fn) |
| Reads algorithm parameters from a file storage.
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virtual void | save (const String &filename) const |
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void | write (const Ptr< FileStorage > &fs, const String &name=String()) const |
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virtual void | write (FileStorage &fs) const |
| Stores algorithm parameters in a file storage.
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void | write (FileStorage &fs, const String &name) const |
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Disparity map filter based on Weighted Least Squares filter (in form of Fast Global Smoother that is a lot faster than traditional Weighted Least Squares filter implementations) and optional use of left-right-consistency-based confidence to refine the results in half-occlusions and uniform areas.
◆ getConfidenceMap()
virtual Mat cv::ximgproc::DisparityWLSFilter::getConfidenceMap |
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pure virtual |
Python: |
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| cv.ximgproc.DisparityWLSFilter.getConfidenceMap( | | ) -> | retval |
Get the confidence map that was used in the last filter call. It is a CV_32F one-channel image with values ranging from 0.0 (totally untrusted regions of the raw disparity map) to 255.0 (regions containing correct disparity values with a high degree of confidence).
◆ getDepthDiscontinuityRadius()
virtual int cv::ximgproc::DisparityWLSFilter::getDepthDiscontinuityRadius |
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pure virtual |
Python: |
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| cv.ximgproc.DisparityWLSFilter.getDepthDiscontinuityRadius( | | ) -> | retval |
DepthDiscontinuityRadius is a parameter used in confidence computation. It defines the size of low-confidence regions around depth discontinuities.
◆ getLambda()
virtual double cv::ximgproc::DisparityWLSFilter::getLambda |
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pure virtual |
Python: |
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| cv.ximgproc.DisparityWLSFilter.getLambda( | | ) -> | retval |
Lambda is a parameter defining the amount of regularization during filtering. Larger values force filtered disparity map edges to adhere more to source image edges. Typical value is 8000.
filter parameters
◆ getLRCthresh()
virtual int cv::ximgproc::DisparityWLSFilter::getLRCthresh |
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pure virtual |
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| cv.ximgproc.DisparityWLSFilter.getLRCthresh( | | ) -> | retval |
LRCthresh is a threshold of disparity difference used in left-right-consistency check during confidence map computation. The default value of 24 (1.5 pixels) is virtually always good enough.
confidence-related parameters
◆ getROI()
virtual Rect cv::ximgproc::DisparityWLSFilter::getROI |
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pure virtual |
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| cv.ximgproc.DisparityWLSFilter.getROI( | | ) -> | retval |
Get the ROI used in the last filter call.
◆ getSigmaColor()
virtual double cv::ximgproc::DisparityWLSFilter::getSigmaColor |
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pure virtual |
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| cv.ximgproc.DisparityWLSFilter.getSigmaColor( | | ) -> | retval |
SigmaColor is a parameter defining how sensitive the filtering process is to source image edges. Large values can lead to disparity leakage through low-contrast edges. Small values can make the filter too sensitive to noise and textures in the source image. Typical values range from 0.8 to 2.0.
◆ setDepthDiscontinuityRadius()
virtual void cv::ximgproc::DisparityWLSFilter::setDepthDiscontinuityRadius |
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int | _disc_radius | ) |
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pure virtual |
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| cv.ximgproc.DisparityWLSFilter.setDepthDiscontinuityRadius( | _disc_radius | ) -> | None |
◆ setLambda()
virtual void cv::ximgproc::DisparityWLSFilter::setLambda |
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double | _lambda | ) |
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pure virtual |
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| cv.ximgproc.DisparityWLSFilter.setLambda( | _lambda | ) -> | None |
◆ setLRCthresh()
virtual void cv::ximgproc::DisparityWLSFilter::setLRCthresh |
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int | _LRC_thresh | ) |
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pure virtual |
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| cv.ximgproc.DisparityWLSFilter.setLRCthresh( | _LRC_thresh | ) -> | None |
◆ setSigmaColor()
virtual void cv::ximgproc::DisparityWLSFilter::setSigmaColor |
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double | _sigma_color | ) |
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pure virtual |
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| cv.ximgproc.DisparityWLSFilter.setSigmaColor( | _sigma_color | ) -> | None |
The documentation for this class was generated from the following file: