ShadingNet: Image Intrinsics by Fine-Grained Shading Decomposition

In general, intrinsic image decomposition algorithms interpret shading as one unified component including all photometric effects. As shading transitions are generally smoother than reflectance (albedo) changes, these methods may fail in distinguishing strong photometric effects from reflectance variations. Therefore, in this paper, we propose to decompose the shading component into direct (illumination) and indirect shading (ambient light and shadows) subcomponents. The aim is to distinguish strong photometric effects from reflectance variations. An end-to-end deep convolutional neural network (ShadingNet) is proposed that operates in a fine-to-coarse manner with a specialized fusion and refinement unit exploiting the fine-grained shading model. It is designed to learn specific reflectance cues separated from specific photometric effects to analyze the disentanglement capability. A large-scale dataset of scene-level synthetic images of outdoor natural environments is provided with fine-grained intrinsic image ground-truths. Large scale experiments show that our approach using fine-grained shading decompositions outperforms state-of-the-art algorithms utilizing unified shading on NED, MPI Sintel, GTA V, IIW, MIT Intrinsic Images, 3DRMS and SRD datasets.Comment: Submitted to International Journal of Computer Vision (IJCV

The geological and depositional setting of the Brunner coal measures, New Zealand, and the influence of these factors on seam thickness and petrological characteristics of Brunner coals

The Brunner Coal Measures comprise up to 300 metres of sandstone, mudstone, coal and conglomerate at the base of an Eo-Oligocene transgressive sequence in North Westland. They generally contain one laterally extensive coal seam that is locally up to fifteen metres thick. Seam-splitting is generally simple but in places complex multiple splitting occurs and coal of mineable thickness may be absent. Regional differences in total thickness and local variations in seam thickness largely reflects variations in local rates of subsidence and syn-depositional faulting

Mineralogy and IR spectroscopy of the Tagish Lake C2 chondrite and enstatite chondrites

Sample-correlated X-ray diffraction (XRD) and diffuse-reflectance Fourier- transform infrared (DRIFTS) spectra were collected for seven samples of the Tagish Lake C2 chondrite and thirteen enstatite chondrites. A reconnaissance of the Tagish Lake chondrite was carried out using micro-XRD, SEM-EDX and EPMA. Modal mineral abundances were obtained from XRD data via Rietveld refinement. Grain densities were calculated for each sample based on the modal abundances. DRIFTS spectra are analogous to remote-sensing emission IR spectra, facilitating comparison with astronomical observations. Tagish Lake was found to be more varied in major mineralogy than has previously been reported. In addition to the documented carbonate-rich and carbonate-poor lithologies, a magnetite- and- sulphide-rich lithology, and a carbonaterich, siderite-dominated lithology have been observed. Several Tagish Lake samples may contain extraterrestrial sulphates. Terrestrially altered enstatite chondrites may be analogous to the regolith of certain rare M- and E-type asteroids (“W-class”) which possess a spectral feature consistent with hydrated minerals

Effects of Regolith Properties on UV/VIS Spectra and Implications for Lunar Remote Sensing

Lunar regolith chemistry, mineralogy, various maturation factors, and grain size dominate the reflectance of the lunar surface at ultraviolet (UV) to visible (VIS) wavelengths. These regolith properties leave unique fingerprints on reflectance spectra in the form of varied spectral shapes, reflectance intensity values, and absorption bands. With the addition of returned lunar soils from the Apollo and Luna missions as ground truth, these spectral fingerprints can be used to derive maps of global lunar chemistry or mineralogy to analyze the range of basalt types on the Moon, their spatial distribution, and source regions for clues to lunar formation history and evolution. The Lunar Reconnaissance Orbiter Camera (LROC) Wide Angle Camera (WAC) is the first lunar imager to detect bands at UV wavelengths (321 and 360 nm) in addition to visible bands (415, 566, 604, 643, and 689 nm). This dissertation uses a combination of laboratory and remote sensing studies to examine the relation between TiO2 concentration and WAC UV/VIS spectral ratios and to test the effects of variations in lunar chemistry, mineralogy, and soil maturity on ultraviolet and visible wavelength reflectance. Chapter 1 presents an introduction to the dissertation that includes some background in lunar mineralogy and remote sensing. Chapter 2 covers coordinated analyses of returned lunar soils using UV-VIS spectroscopy, X-ray diffraction, and micro X-ray fluorescence. Chapter 3 contains comparisons of local and global remote sensing observations of the Moon using LROC WAC and Clementine UVVIS TiO2 detection algorithms and Lunar Prospector (LP) Gamma Ray Spectrometer (GRS)-derived FeO and TiO2 concentrations. While the data shows effects from maturity and FeO on the UV/VIS detection algorithm, a UV/VIS relationship remains a simple yet accurate method for TiO2 detection on the Moon

Micro-Computed Tomography Semi-Empirical Beam Hardening Correction: Method And Application To Meteorites

X-ray micro-computed tomography (μCT) is able to non-destructively provide high- resolution 3D images of the internal structures of dense materials such as meteorites. The widespread availability of instruments capable of biomedical micro-computed tomography means there is ample access to scanners for the investigation of geomaterials, but the scan data can be susceptible to artifacts such as beam hardening, a consequence of high X-ray attenuation in these dense materials. A semi-empirical correction method for beam hardening and scatter that can be straightforwardly applied to available biomedical scanners is proposed and evaluated. This method uses aluminum as a single calibration material to significantly reduce or remove signal intensity errors (i.e. cupping) that occur as a result of beam hardening artifacts. X-ray transmission data are linearized using custom software. Results show that it is possible through careful analysis to determine an effective method of artifact correction for specified protocols using this implementation. Following correction and validation, this technique is applied to imaging of meteorite samples. Four meteorites are examined using μCT in combination with this processing technique: Three ordinary chondrites (Grimsby, Gao-Guenie, and Ozona) and an olivine diogenite (NWA 5480). Information from μCT is compared to that of traditional methods of analysis of meteoritic samples, and the advantages and disadvantages are discussed