...

LIS Filtering - filtering and classification

This package contains tools for outlier removal from points clouds, point cloud filtering based on attributes, majority filtering of point clouds, point cloud classification based on raster surfaces and morphological filtering of raster data sets.

Tool: Attribute Filter

Features
• filtering of a point cloud based on attribute values
• up to three filter attributes, evaluated one after the other
• filter methods: drop points, invalidate points, binary flag
• filter types: lower limit (min), upper limit (max), min/max, list of invalid values, list of valid values
Applications
• point cloud filtering / subsetting
• point cloud classification

Tool: Filter Point Cloud with Grid Surface

Features
• classification of a point cloud based on the elevation difference (offset) to a filter surface provided as grid data set
• AOI is defined by grid extent
• support of multiple offsets (point cloud slicing)
• elevation difference is measured either to grid cell or to triangulation of 3x3 neighborhood
• output: either only points matching the filter criteria or all points with additional classification attribute
Applications
• point cloud classification
• point cloud height slicing
• point cloud filtering / subsetting

Tool: Majority Filter

Features
• application of a majority filter to a point cloud attribute
• majority is calculated from the local neighborhood of each point (2D or 3D)
• an inner radius may be specified to transform the shape of the neighborhood to an annulus (a donut)
• majority threshold (percent), optional
• attribute value range to process, optional
• attribute values range to include in majority calculation, optional
Applications
• classification cleanup / improvement
• noise removal

Tool: Morphological Filter

Features
• morphological filter operations for grid data sets: erosion, dilation, opening, and closing
• square or circular kernel
• user defined kernel radius
• minimum elevation difference threshold, optional
• filling of NoData gaps, optional
Applications
• removal of small objects
• boundary detection
• opening or closing of gaps

Tool: Progressive Morphological Filter

Features
• removal of non-ground measurements from a grid data set
• gradually increasing filter size and elevation difference thresholds
• adaptation of the filter proposed by ZHANG, K., CHEN, S.-C., WHITMAN, D., SHYU, M.-L., YAN, J. & C. ZHANG (2003)
Applications
• DTM generation

Tool: Remove Duplicate Points

Features
• removal of duplicate points from a point cloud by local neighborhood analysis (3D)
• several options to decide which point found in the neighborhood should be retained
• attribute based selection criterion, optional
• removal of all duplicates (including the search point), optional
Applications
• removal of noise and/or erroneous points
• point cloud pre-processing

Tool: Remove Isolated Points

Features
• detection of outliers in a point cloud by local neighborhood analysis (3D)
• maximum number of points in neighborhood thresholding
Applications
• removal or labelling of outliers
• point cloud pre-processing

Tool: Remove Low and Air Points

Features
• removal of outliers from a point cloud by local neighborhood analysis (2D/3D)
• seperate elevation thresholds and class labels for low and air points
• detection of point groups/clusters (instead of individual points), optional
• iterative filtering (filter is applied several times), optional
Applications
• removal of outliers from point clouds
• point cloud pre-processing

Tool: Remove Outliers

Features
• removal of outliers from a point cloud by local neighborhood analysis (k nearest neighbors)
• detection of negative outliers by elevation ranking and thresholding
• detection of positive outliers by elevation difference
Applications
• removal of outliers from point clouds
• point cloud pre-processing