Abstract
Abstract. The purpose of this paper is to analyze how optical pre-processing with polarizing filters and digital pre-processing with HDR imaging, may improve the automated 3D modeling pipeline based on SFM and Image Matching, with special emphasis on optically non-cooperative surfaces of shiny or dark materials. Because of the automatic detection of homologous points, the presence of highlights due to shiny materials, or nearly uniform dark patches produced by low reflectance materials, may produce erroneous matching involving wrong 3D point estimations, and consequently holes and topological errors on the mesh originated by the associated dense 3D cloud. This is due to the limited dynamic range of the 8 bit digital images that are matched each other for generating 3D data. The same 256 levels can be more usefully employed if the actual dynamic range is compressed, avoiding luminance clipping on the darker and lighter image areas. Such approach is here considered both using optical filtering and HDR processing with tone mapping, with experimental evaluation on different Cultural Heritage objects characterized by non-cooperative optical behavior. Three test images of each object have been captured from different positions, changing the shooting conditions (filter/no-filter) and the image processing (no processing/HDR processing), in order to have the same 3 camera orientations with different optical and digital pre-processing, and applying the same automated process to each photo set.
Highlights
1.1 Photogrammetry with polarizing filtersLight is generally idealized as a sequence of photons, each one representing a short piece of electromagnetic wave
In aerial applications (Paine et al, 2012) have demonstrated that polarizing filters improve imaging on water and allow to penetrate haze, while in closerange photogrammetry they have been used for precise detection of shiny aluminum structures and retroreflective targets in aerospace industry (Wells et al, 2005)
The masks were exported in order to use them for all the images acquired from a certain position with the different levels of image preprocessing
Summary
1.1 Photogrammetry with polarizing filtersLight is generally idealized as a sequence of photons, each one representing a short piece of electromagnetic wave. The direct sunlight has an orientation randomly varying, is not polarized, but the light coming from the blue sky (i.e. reflected from the water molecules suspended in air), is characterized by a specific orientation determined by the dipole structure of water (H2O) When looking at such light from a direction at right angles with respect to the sun rays, such polarization is maximized and a polarizing filter, if rotated orthogonally to the polarizing orientation, will filter out the polarized component of skylight darkening the sky. The landscape below it and the clouds, will be less affected, giving an image with a darker and more dramatic sky, emphasizing the contrast with the clouds (Goldberg, 1992). In aerial applications (Paine et al, 2012) have demonstrated that polarizing filters improve imaging on water and allow to penetrate haze, while in closerange photogrammetry they have been used for precise detection of shiny aluminum structures and retroreflective targets in aerospace industry (Wells et al, 2005)
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