Leica LiDAR scanners output points in the PTX file format. It is often useful to convert this format to a standard VTK point cloud or mesh format before processing. We propose a new class, vtkPTXReader, to provide this functionality.

A Leica PTX Reader for VTK

This document presents a set of classes (vtkPointSetSurfaceReconstruction, vtkVoxelizePolyData) to produce a surface from an oriented point set. These classes are implemented as VTK filters. A Paraview plugin interface is provided to allow extremely easy experimentation with the new functionality. We propose these classes as an addition to the Visualization Toolkit. The code is available here: https://github.com/daviddoria/PointSetSurfaceReconstruction

Point Set Surface Reconstruction for VTK

This article describes the ITK implementation of a Normalized Gradient Fields
based image-to-image metric. Some properties of the metric are discussed and example registrations are presented.

An ITK implementation of the Normalized Gradient Field Image to Image Metric

This document presents a set of classes (vtkPhysicalCamera, vtkImageCamera) to enable a camera and an image acquired by that camera to be visualized in a 3D scene. Two situations where one would want to visualize camaras with associated images are range data analysis and 3D scene reconstruction from images (structure from motion). The classes presented in this paper are implemented using tools from VTK.

Using and Visualizing Projective Cameras in VTK

Voodoo is a popular, free structure from motion software package. It takes several, ordered images as input and computes the camera parameters of each image as well as a point cloud of an estimate of the 3D structure of the scene. This document presents a set of classes (vtkCalibratedImageCollection, vtkCalibratedImageCollectionReader, vtkVoodooReader) to enable a set of images and their associated 3D scene to be viewed in the same space. These classes are implemented using tools from VTK. The current code can be found at https://github.com/daviddoria/vtkVoodooReader .

A Voodoo Reader and Viewer for VTK

The Fourier transform of the convolution of two images is equal to the product of their
Fourier transform. With this definition, it is possible to create a convolution filter
based on the Fast Fourier Transform (FFT). The interesting complexity characteristics of
this transform gives a very efficient convolution filter for large kernel images.

This paper provides such a filter, as well as a detailed description of the implementation
choices and a performance comparison with the "simple" itk::ConvolutionImageFilter.


FFT based convolution

This document presents an implementation of the Poisson surface reconstruction algorithm in the VTK framework. (This code was, with permission, adapted directly from the original implementation by Kazhdan, Bolitho, and Hugues. The original implementation can be found here http://www.cs.jhu.edu/~misha/Code/IsoOctree/). We present a class, vtkPoissonReconstruction, which produces a surface from an oriented point set. A Paraview plugin interface is provided to allow extremely easy experimentation with the new functionality. We propose these classes as an addition to the Visualization Toolkit.

Poisson Surface Reconstruction for VTK

This document presents an implementation of a stratified mesh sampling algorithm in the VTK framework. This code was adapted directly from the original implementation by Diego Nehab, with permission. We present a class, vtkStratifiedSampling, which uniformly samples a mesh. A Paraview plugin interface is provided to allow extremely easy experimentation with the new functionality. We propose these classes as an addition to the Visualization Toolkit.

Stratified Mesh Sampling for VTK

Segmenting images into "super pixels" is lately a very hot topic. One implementation of such a technique is by Felzenszwalb and Huttenlocher. We propose a new class, vtkSuperPixelSegmentation, which has wrapped Felzenszwalb's code (with permission) to provide this functionality in the VTK framework. The latest version includes an ITK filter as well as the original VTK filter. A GUI is also now available to interactively set the filter parameters and see the resulting segments. The code is available here: https://github.com/daviddoria/SuperPixelSegmentation.

Graph Cuts Based Super Pixel Segmentation for VTK

Several kind of noise can be found in real images, mostly depending on the modality
of acquisition. It is often useful to be able to simulate that noise, for example
to test the behavior of an algorithm in the presence of a known amount of noise.

This contribution provides the filters to generate four kind of noise -- additive
gaussian, shot, speckle and salt and pepper -- as well as a PSNR calculator.
