Hyperspectral Unmixing with Endmember Variability using Partial Membership Latent Dirichlet Allocation

The application of Partial Membership Latent Dirichlet Allocation(PM-LDA) for hyperspectral endmember estimation and spectral unmixing is presented. PM-LDA provides a model for a hyperspectral image analysis that accounts for spectral variability and incorporates spatial information through the use of superpixel-based 'documents.' In our application of PM-LDA, we employ the Normal Compositional Model in which endmembers are represented as Normal distributions to account for spectral variability and proportion vectors are modeled as random variables governed by a Dirichlet distribution. The use of the Dirichlet distribution enforces positivity and sum-to-one constraints on the proportion values. Algorithm results on real hyperspectral data indicate that PM-LDA produces endmember distributions that represent the ground truth classes and their associated variability

Semi-supervised interactive unmixing for hyperspectral image analysis

In the past several decades, hyperspectral imaging has drawn a lot of attention in the field of remote sensing. Yet, due to low spatial resolutions of hyperspectral imagers, often the response from more than one surface material can be found in some hyperspectral pixels. These pixels are called mixed pixels. Mixed pixels bring challenges to traditional pixel-level applications, such as identification and detection of ground targets [1, 2]. To address these challenges, hyperspectral unmixing is often an important step during analysis of hyperspectral imagery. Hyperspectral unmixing is the task of decomposing each pixel into a set of pure material signatures (called endmembers) with the corresponding proportions of each material found in each pixel. In this thesis, novel hyperspectral unmixing approaches are proposed that leverage interactive labeling and semi-supervised approaches to improve unmixing results

Efficient infrared upconversion via a ladder-type atomic configuration

We have demonstrated experimentally that infrared light at 1529.4nm can be converted into the visible at 780nm with 54% efficiency through a ladder-type atomic configuration in 85Rb. Specifically we theoretically analyze that high efficiency is due to the large nonlinear dispersion of the index of refraction from the off-resonant enhancement in a four-wave mixing (FWM) process. By using two perpendicular polarized pump fields, the coherence of two FWM processes in this configuration is verified.Comment: The new version is published in Journal of Modern Optic