1. 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

2. 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

3. 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

4. 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

5. 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

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

7. 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

8. Thank You!