No abstract

No abstract

ABSTRACT:Reconstructing the 3D profile from a set of UAV-based images can obtain hyperspectral information, as well as the 3D coordinate of any point on the profile. Our images are captured from the Cubert UHD185 (UHD) hyperspectral camera, which is a new type of high-speed onboard imaging spectrometer. And it can get both hyperspectral image and panchromatic image simultaneously. The panchromatic image have a higher spatial resolution than hyperspectral image, but each hyperspectral image provides considerable information on the spatial spectral distribution of the object. Thus there is an opportunity to derive a high quality 3D point cloud from panchromatic image and considerable spectral information from hyperspectral image. The purpose of this paper is to introduce our processing chain that derives a database which can provide hyperspectral information and 3D position of each point. First, We adopt a free and open-source software, Visual SFM which is based on structure from motion (SFM) algorithm, to recover 3D point cloud from panchromatic image. And then get spectral information of each point from hyperspectral image by a self-developed program written in MATLAB. The production can be used to support further research and applications. INSTRUCTIONHyperspectral images can be used for finding objects, identifying materials, or detecting spatial processes. Compared to RGB images, which only contain three bands of the visual part of the electromagnetic spectrum (red, green and blue light). The hyperspectral image contains continuous hundreds bands of the electromagnetic spectrum in the sensor's wavelength range. And it can provide considerable information on the spatial spectral distribution of the object.Traditionally, Hyperspectral images are acquired with satellites(Clark, 2016), airborne sensors (Quemada et al., 2014)or field spectrometers (Numata et al., 2008). Recently, with the size and weight of hyperspectral sensors have been shrinking and have been carried onboard of UAVs. Such as a new type of hyperspectral cameras like the UHD has been used for UAV remote sensing.In computer vision, 3D reconstruction is the process of recovering the shape and profile of real objects. This process can be accomplished either by active or passive methods. Active methods derive the depth map using methods of structure light, laser range finder and radiometric rangefinders, then reconstruct the 3D profile by numerical approximation approach and establish the object in the scene based on model. Although this method can get high quality data, it also requires expensive equipment. In contrast, the development of passive methods provides the opportunity for very low-cost three-dimensional data acquisition. Passive methods measure the radiance reflected or emitted by the object's surface to reconstruct the 3D profile from a set of digital images. Passive methods include structure from motion (SFM), photometric stereo, shape-from-shading etc.The SFM techniques can be used for estimating 3D structure from a series of overlappin...

A newly developed method has been employed to quantify the mechanical behavior of sheet metals (both isotropic and orthotropic) subjected to dynamic bulge loading at strain rates of up to 400 s−1. Using newly developed dynamic bulge testing equipment with stereoscopic imaging, the exact shape of the bulging dome has been obtained and represented using high order polynomials before further constitutive analysis. The bulge profile functions discerned have been used to calculate the actual radius of curvature at the pole, thus replacing the spherical shape generally assumed in traditional bulge test analysis. Furthermore, the calculation of the thickness of the bulge has been improved by employing “dome volume” approaches. Effective strain and stress at the dome’s pole have been calculated considering both isotropic and orthotropic materials. The effect of gage length on the obtained values of strain and stress has been assessed.