Image Orientation

This paper investigates the use of different greyscale conversion algorithms to decolourize colour images as input for two Structure-from-Motion (SfM) software packages. Although SfM software commonly works with a wide variety of frame imagery (old and new, colour and greyscale, airborne and terrestrial, large-and small scale), most programs internally convert the source imagery to single-band, greyscale images. This conversion is often assumed to have little, if any, impact on the final outcome.
To verify this assumption, this article compares the output of an academic and a commercial SfM software package using seven different collections of architectural images. Besides the conventional 8-bit true-colour JPEG images with embedded sRGB colour profiles, for each of those datasets, 57 greyscale variants were computed with different colour-to-greyscale algorithms. The success rate of specific colour conversion approaches can, therefore, be compared with the commonly implemented colour-to-greyscale algorithms (luma Y’601, luma Y’709, or luminance CIE Y), both in terms of the applied feature extractor as well as of the specific image content (as exemplified by the two different feature descriptors and the various image collections, respectively).
Although the differences can be small, the results clearly indicate that certain colour-to-greyscale conversion algorithms in an SfM-workflow constantly perform better than others. Overall, one of the best performing decolourization algorithms turns out to be a newly developed one.

An integrated analysis of recent satellite imageries and dated aerial photos demonstrated to be a good investigation tool (Gallo et al., 2009) for the identification of new sites and for the assessment of landscape changes of wide archaeological areas in Ethiopia.In the Melka Kunture archaeological sequence, the obsidian exploitation represents a leitmotiv during the last 1.7 Myr and the first known example of Oldowan utilization (Piperno et al., 2009).The primary nearest obsidian source, the site of Balchit, 7 km North from Melka Kunture, is a dome-flow dated to 4.37 ± 0.07 Myr (Chernet et al., 1998). Large areas of the Balchit site are covered by secondary obsidian debris resulting from the erosion of primary sources.The proximity between primary and secondary Balchit obsidian sources and the high quality of this raw material, easily available in large quantity, represent a unique condition in the framework of the Oldowan and Acheulian East African sites (Piperno et al., 2009).In order to evaluate the human impact on the multitemporal change of obsidian sources, the land use of the study area, following the CORINE Land Cover Nomenclature, has been classified from aerial photos and IKONOS II imageries, respectively dated to 1972 and 2006. The accurate positioning of the primary and secondary sources and their extent have been measured thanks to the multispectral characteristics and to the high spatial resolution of the available imageries.Satellite scenes, covering an area of about 100 km2, have been also utilized in stereoscopy for the creation of the new topographic map, at the scale of 1:10,000, and of the Digital Elevation Model (DEM).Images orientation has been performed through the use of Rational Polynomial Coefficients (RPC) which accuracy has been improved by the availability of Ground Control Points (GCPs) properly measured during a DGPS survey. Then, the images have been orthorectified and radiometrically and spectrally enhanced in order to favour the recognition of obsidian presence, in respect with ground observations collected during fieldworks.Photointerpretation and semi-automatic classification processes of images have been performed with the support of spectral signatures of obsidian samples recorded by a FieldSpec Pro spectroradiometer, ranging in the visible-short wave infrared electromagnetic interval (0.4–2.5 μm).

: From left to right: one of the 40 images captured by a handheld camera under natural conditions; the recovered hair rendered with the recovered diffuse color; a fraction of the longest recovered hair fibers rendered with the recovered diffuse color to show the hair threads; the recovered hair rendered with an artificial constant color.

In the photogrammetry field, interest in region detectors, which are widely used in Computer Vision, is quickly increasing due to the availability of new techniques. Images acquired by Mobile Mapping Technology, Oblique Photogrammetric Cameras or Unmanned Aerial Vehicles do not observe normal acquisition conditions. Feature extraction and matching techniques, which are traditionally used in photogrammetry, are usually inefficient for these applications as they are unable to provide reliable results under extreme geometrical conditions (convergent taking geometry, strong affine transformations, etc.) and for bad-textured images. A performance analysis of the SIFT technique in aerial and close-range photogrammetric applications is presented in this paper. The goal is to establish the suitability of the SIFT technique for automatic tie point extraction and approximate DSM (Digital Surface Model) generation. First, the performances of the SIFT operator have been compared with those provided by feature extraction and matching techniques used in photogrammetry. All these techniques have been implemented by the authors and validated on aerial and terrestrial images. Moreover, an auto-adaptive version of the SIFT operator has been developed, in order to improve the performances of the SIFT detector in relation to the texture of the images. The Auto-Adaptive SIFT operator (A 2 SIFT) has been validated on several aerial images, with particular attention to large scale aerial images acquired using mini-UAV systems.