arXiv subjects

Joseph L. Garrett

Publications and source records attributed to Joseph L. Garrett.

8 recordsLinked to original sources

arXiv2026

Hyperspectral Unmixing Hierarchies

Unmixing reveals the spatial distribution and spectral details of different constituents, called endmembers, in a hyperspectral image. Because unmixing has limited ground truth requirements, can accommodate mixed pixels, and is closely tied to light propagation, it is a uniquely powerful tool for analyzing hyperspectral images. However, spectral variability inhibits unmixing performance, the proper way to determine the number of endmembers is ambiguous, and the clarity of the endmembers degrades as more are included. Hierarchical structure is a possible solution to all three problems. Here, hierarchical unmixing is defined by imposing a hierarchical abundance sum constraint on Deep Nonnegative Matrix Factorization. Binary Linear Unmixing Tactile Hierarchies (BLUTHs) solve the hierarchical unmixing problem with a simple network architecture. Sparsity modulation unmixing growth tailors the topology of a BLUTH to each scene. The structure imposed by BLUTHs allows endmembers with varying levels of spectral contrast to be revealed, mitigating the challenge of spectral variability. The performance of BLUTHs exceeds state-of-the-art unmixing algorithms on laboratory scenes, particularly with regard to abundance estimation, while their performance remains competitive on remote sensing scenes. In addition, ocean color unmixing by BLUTHs is demonstrated on hyperspectral scenes from the HYPSO and PACE satellites.

cs.CV↗

arXiv2024

Semantic Segmentation in Satellite Hyperspectral Imagery by Deep Learning

Satellites are increasingly adopting on-board AI to optimize operations and increase autonomy through in-orbit inference. The use of Deep Learning (DL) models for segmentation in hyperspectral imagery offers advantages for remote sensing applications. In this work, we train and test 20 models for multi-class segmentation in hyperspectral imagery, selected for their potential in future space deployment. These models include 1D and 2D Convolutional Neural Networks (CNNs) and the latest vision transformers (ViTs). We propose a lightweight 1D-CNN model, 1D-Justo-LiuNet, which outperforms state-of-the-art models in the hypespectral domain. 1D-Justo-LiuNet exceeds the performance of 2D-CNN UNets and outperforms Apple's lightweight vision transformers designed for mobile inference. 1D-Justo-LiuNet achieves the highest accuracy (0.93) with the smallest model size (4,563 parameters) among all tested models, while maintaining fast inference. Unlike 2D-CNNs and ViTs, which encode both spectral and spatial information, 1D-Justo-LiuNet focuses solely on the rich spectral features in hyperspectral data, benefitting from the high-dimensional feature space. Our findings are validated across various satellite datasets, with the HYPSO-1 mission serving as the primary case study for sea, land, and cloud segmentation. We further confirm our conclusions through generalization tests on other hyperspectral missions, such as NASA's EO-1. Based on its superior performance and compact size, we conclude that 1D-Justo-LiuNet is highly suitable for in-orbit deployment, providing an effective solution for optimizing and automating satellite operations at edge.

cs.CV↗

arXiv2024

Quick unsupervised hyperspectral dimensionality reduction for earth observation: a comparison

Dimensionality reduction can be applied to hyperspectral images so that the most useful data can be extracted and processed more quickly. This is critical in any situation in which data volume exceeds the capacity of the computational resources, particularly in the case of remote sensing platforms (e.g., drones, satellites), but also in the case of multi-year datasets. Moreover, the computational strategies of unsupervised dimensionality reduction often provide the basis for more complicated supervised techniques. Seven unsupervised dimensionality reduction algorithms are tested on hyperspectral data from the HYPSO-1 earth observation satellite. Each particular algorithm is chosen to be representative of a broader collection. The experiments probe the computational complexity, reconstruction accuracy, signal clarity, sensitivity to artifacts, and effects on target detection and classification of the different algorithms. No algorithm consistently outperformed the others across all tests, but some general trends regarding the characteristics of the algorithms did emerge. With half a million pixels, computational time requirements of the methods varied by 5 orders of magnitude, and the reconstruction error varied by about 3 orders of magnitude. A relationship between mutual information and artifact susceptibility was suggested by the tests. The relative performance of the algorithms differed significantly between the target detection and classification tests. Overall, these experiments both show the power of dimensionality reduction and give guidance regarding how to evaluate a technique prior to incorporating it into a processing pipeline.

eess.IV↗

arXiv2019

Sensitivity and accuracy of Casimir force measurements in air

Quantum electrodynamic fluctuations cause an attractive force between metallic surfaces. At separations where the finite speed of light affects the interaction, it is called the Casimir force. Thermal motion determines the fundamental sensitivity limits of its measurement at room temperature, but several other systematic errors contribute uncertainty as well and become more significant in air relative to vacuum. Here we discuss the viability of several measurement techniques in air (force modulation, frequency modulation, and quasi-static deflection), characterize their sensitivity and accuracy by identifying several dominant sources of uncertainty, and compare the results to the fundamental sensitivity limits dictated by thermal motion and to the uncertainty inherent to calculations of the Casimir force. Finally, we explore prospects for mitigating the sources of uncertainty to enhance the range and accuracy of Casimir force measurements.

quant-ph↗

arXiv2017

Effect of lateral tip motion on multifrequency atomic force microscopy

In atomic force microscopy (AFM), the angle relative to the vertical ($θ_{i}$) that the tip apex of a cantilever moves is determined by the tilt of the probe holder and the geometries of the cantilever and actuated eigenmode $i$. Even though the effects of $θ_{i}$ on static and single-frequency AFM are known (increased effective spring constant, sensitivity to sample anisotropy, etc), the higher eigenmodes used in multifrequency force microscopy lead to additional effects that have not been fully explored. Here we use Kelvin probe force microscopy (KPFM) to investigate how $θ_{i}$ affects not only the signal amplitude and phase, but can also lead to behaviors such as destabilization of the KPFM voltage feedback loop. We find that longer cantilevers and modified sample orientations improve voltage feedback loop stability, even though variations to scanning parameters such as cantilever shake amplitude and lift height do not.

cond-mat.mes-hall↗

arXiv2016

Mid-infrared time-resolved photoconduction in black phosphorus

Black phosphorus has attracted interest as a material for use in optoelectronic devices due to many favorable properties such as a high carrier mobility, field-effect, and a direct bandgap that can range from 0.3 eV in its bulk crystalline form to 2 eV for a single atomic layer. The low bandgap energy for bulk black phosphorus allows for direct transition photoabsorption that enables detection of light out to mid-infrared frequencies. In this work we characterize the room temperature optical response of a black phosphorus photoconductive detector at wavelengths ranging from 1.56 $μ$m to 3.75 $μ$m. Pulsed autocorrelation measurements in the near-infrared regime reveal a strong, sub-linear photocurrent nonlinearity with a response time of 1 ns, indicating that gigahertz electrical bandwidth is feasible. Time resolved photoconduction measurements covering near- and mid-infrared frequencies show a fast 65 ps rise time, followed by a carrier relaxation with a time scale that matches the intrinsic limit determined by autocorrelation. The sublinear photoresponse is shown to be caused by a reduction in the carrier relaxation time as more energy is absorbed in the black phosphorus flake and is well described by a carrier recombination model that is nonlinear with excess carrier density. The device exhibits a measured noise-equivalent power of 530 pW/$\sqrt{\text{Hz}}$ which is the expected value for Johnson noise limited performance. The fast and sensitive room temperature photoresponse demonstrates that black phosphorus is a promising new material for mid-infrared optoelectronics.

cond-mat.mtrl-sci↗

arXiv2016

Fast, high-resolution surface potential measurements in air with heterodyne Kelvin probe force microscopy

Kelvin probe force microscopy (KPFM) adapts an atomic force microscope to measure electric potential on surfaces at nanometer length scales. Here we demonstrate that Heterodyne-KPFM enables scan rates of several frames per minute in air, and concurrently maintains spatial resolution and voltage sensitivity comparable to frequency-modulation KPFM, the current spatial resolution standard. Two common classes of topography-coupled artifacts are shown to be avoidable with H-KPFM. A second implementation of H-KPFM is also introduced, in which the voltage signal is amplified by the first cantilever resonance for enhanced sensitivity. The enhanced temporal resolution of H-KPFM can enable the imaging of many dynamic processes, such as such as electrochromic switching, phase transitions, and device degredation (battery, solar, etc.), which take place over seconds to minutes and involve changes in electric potential at nanometer lengths.

cond-mat.mes-hall↗

arXiv2014

The effect of patch potentials in Casimir force measurements determined by heterodyne Kelvin probe force microscopy

Measurements of the Casimir force require the elimination of electrostatic interactions between the surfaces. However, due to electrostatic patch potentials, the voltage required to minimize the total force may not be sufficient to completely nullify the electrostatic interaction. Thus, these surface potential variations cause an additional force, which can obscure the Casimir force signal. In this paper, we inspect the spatially varying surface potential (SP) of e-beamed, sputtered, sputtered and annealed, and template stripped gold surfaces with Heterodyne Amplitude Modulated Kelvin Probe Force Microscopy (HAM-KPFM). It is demonstrated that HAM-KPFM improves the spatial resolution of surface potential measurements compared to Amplitude Modulated Kelvin Probe Force Microscopy (AM-KPFM). We find that patch potentials vary depending on sample preparation, and that the calculated pressure can be similar to the pressure difference between Casimir force calculations employing the plasma and Drude models.

cond-mat.other↗