Presence Of Obscuration Research Articles

Multi-spectral SWIR lidar for imaging and spectral discrimination through partial obscurations.

We have developed a multi-spectral SWIR lidar system capable of measuring simultaneous spatial-spectral information for imaging and spectral discrimination through partial obscurations. We employ objects in the presence and absence of a series of obscurants to evaluate the capability of the system in classifying the objects of interest based on spectral and range information. We employ a principal component analysis-based algorithm in classifying the objects and quantifying the accuracy of detection under various obscured scenarios. The merits of multi-spectral lidar over hyperspectral imaging are highlighted for target identification in the presence of obscurants.

Light Transport Induced Domain Adaptation for Semantic Segmentation in Thermal Infrared Urban Scenes

Semantic segmentation in urban scenes is widely used in applications of intelligent transportation systems (ITS). In urban scenes, thermal infrared (TIR) images can be captured in weak illumination conditions or in the presence of obscuration (e.g., light fog, smoke). Therefore, TIR images have great potential to endow automated intelligent vehicles or assist navigation systems. However, TIR imaging is blurry and low-contrast due to the absorption by atmospheric gases and heat transfer effect. Hence, TIR semantic segmentation in urban scenes has rarely been explored even though it has a wide range of scenarios in ITS. To overcome this limitation, we analyze the light transport of TIR light. Our analysis reveals that contours are the reliable features shared by TIR and Visible Spectrum (VS) light. Inspired by this, we attempt to transfer joint features from VS domain to TIR domain. Thus, we propose a curriculum domain adaptation method to guide the TIR urban scene semantic segmentation task from VS domain through contours. Moreover, to evaluate the proposed model, we build TIR-SS: an open-for-request dataset consisting of TIR images and pixel level annotations of 8 classes in urban scenes. Qualitative and quantitative experimental results on the dataset indicate that the proposed domain adaptation method outperforms related methods on this TIR semantic segmentation task.

DIGITAL IMAGE ANALYSIS OF BURNING DROPLETS IN THE PRESENCE OF BACKLIGHT DIFFRACTION AND SOOT

Approaches for analyzing digital images of moving and burning fuel droplets, with the goal of accurately measuring droplet edge coordinates, are discussed. Strategies for locating droplet edges in the presence of obscuration from soot and also backlight diffraction at the droplet edge are described. An outlier detection method is employed to identify outliers in droplet edge coordinates, and the resulting data can have significantly smaller standard deviations in droplet diameters if outliers are rejected, especially for droplets that exhibit significant soot formation. The approaches described herein are applied to images from droplet combustion experiments performed on the International Space Station as well as to synthetic image sequences that were generated to enable the accuracy of the algorithms to be assessed.

Three-dimensional object visualization and detection in low light illumination using integral imaging.

Conventional two-dimensional (2D) imaging systems that operate in the visible spectrum may perform poorly in environments under low light illumination. In this work, we present the potential of passive three-dimensional (3D) integral imaging (II) to perform 3D imaging of a scene under low light conditions in the visible spectrum and without the need for a photon counting or cooled CCD camera. Using dedicated algorithms, we demonstrate that the reconstructed 3D integral image is naturally optimum in a maximum likelihood sense in low light levels and in the presence of detector noise enabling object visualization in the scene. The conventional 2D imaging fails due to the limited number of photons. Using 3D imaging, we demonstrate the potential for 3D detection of objects behind occlusion in a photon-starved scene. To the best of our knowledge, this is the first report of experimentally using II sensing under low illumination conditions for 3D visualization and 3D object detection in the presence of obscurations with a conventional image sensor.

Modeling human search and target acquisition performance: 3. target detection in the presence of obscurants

The effect of dynamically changing visibility conditions on target acquisition is considered. A model is described that takes as input the statistical characterization ofthe obscurant and the physical char acteristics of the target; the output is the probability of detection as a function of time. Analysis indicates that the variation of the obscurant as a function of time greatly affects the predicted target detection times and, hence, the utility of the infrared system in realistic scenarios.

Radiative heat transfer in the presence of obscurations

Radiative heat transfer in the presence of obscurations