@article{wu_kudenov_2017, title={A reconstruction algorithm for three-dimensional object-space data using Spatial-Spectral Multiplexing}, volume={10198}, ISBN={["978-1-5106-0898-6"]}, ISSN={["1996-756X"]}, DOI={10.1117/12.2264643}, abstractNote={This paper presents a reconstruction algorithm for the Spatial-Spectral Multiplexing (SSM) optical system. The goal of this algorithm is to recover the three-dimensional spatial and spectral information of a scene, given that a one-dimensional spectrometer array is used to sample the pupil of the spatial-spectral modulator. The challenge of the reconstruction is that the non-parametric representation of the three-dimensional spatial and spectral object requires a large number of variables, thus leading to an underdetermined linear system that is hard to uniquely recover. We propose to reparameterize the spectrum using B-spline functions to reduce the number of unknown variables. Our reconstruction algorithm then solves the improved linear system via a least- square optimization of such B-spline coefficients with additional spatial smoothness regularization. The ground truth object and the optical model for the measurement matrix are simulated with both spatial and spectral assumptions according to a realistic field of view. In order to test the robustness of the algorithm, we add Poisson noise to the measurement and test on both two-dimensional and three-dimensional spatial and spectral scenes. Our analysis shows that the root mean square error of the recovered results can be achieved within 5.15%.}, journal={ALGORITHMS AND TECHNOLOGIES FOR MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL IMAGERY XXIII}, author={Wu, Zhejun and Kudenov, Michael W.}, year={2017} }
 @inproceedings{zhang_wang_zhao_wu_2016, title={A Svm-based adaptive stance detection method for pedestrian inertial navigation}, booktitle={2016 10th international conference on sensing technology (icst)}, author={Zhang, Z. C. and Wang, H. Y. and Zhao, Z. H. and Wu, Z. J.}, year={2016} }