Hardware Implementation of CTIS Reconstruction Algorithms Jonathan Nation University of Arizona Optical Detection Labs Staff Mentor: Dr. Eustace Dereniak Grad Student : Riley Aumiller Arizona Space Grant Symposium April 19, 2008

What Is A CTIS System? CTIS = Computed Topography Imaging Spectrometer CGH holographic disperser used to create diffraction pattern 3x3, 5x5, or 7x7 dependent on system Re-imaging lens CCD camera Objective Field stop Collimator CGH disperser Images can be reconstructed into data-cubes Contains a snapshot of Spatial and Spectral data Image from Detlab

Reconstruction Algorithms Basically: g and H are known, f is unknown Algorithms are used to approximate H inverse, because the real inverse cannot be found EM : Expectation Maximization g = image vector of m pixels f = image reconstruction / data cube of n voxels H = m x n reconstruction matrix created during calibration

Problems My Work: Reconstruction time: several seconds to minutes Goal is real-time ( 30 fps)‏ System could be used for threat detection / assessment H ~ 4 million x 2.15 million elements H matrix LARGE – must be stored sparsely High input / output bandwidth & memory requirements My Work: Researching different hardware systems to implement EM algorithm FPGA = Field Programmable Gate Array Matlab's Simulink Xilinx System Generator

Picture courtesy of Digilent Inc. & Xilinx Test System Xilinx XUP V2P system chosen Uses Xilinx Virtex 2 Pro FPGA 30,000 logic cells 136 dedicated multipliers USB Input / Output Discounted academic price Picture courtesy of Digilent Inc. & Xilinx

Design Progress Single iteration of EM algorithm completed Uses very small datasets / H-matrix

Future Work Expand Data sets until they are realistic sizes Requires on-board DDR SDRAM memory access Once full size, measure speed of algorithm Implement iterations of algorithm Research other Input / Output methods other than USB Implement alternative reconstruction algorithms in hardware

Thank You!