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The Frequency-Domain Effects of Stochastic Image Foveation in Superpixelating Cameras

The Frequency-Domain Effects of Stochastic Image Foveation in Superpixelating Cameras. Thayne Coffman EE381K-14 May 3, 2005. Review – Motivation and Objective. Superpixellating (“VASI”) cameras Translation of desired resolution to control signal can be done by halftoning

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The Frequency-Domain Effects of Stochastic Image Foveation in Superpixelating Cameras

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  1. The Frequency-Domain Effects of Stochastic Image Foveation in Superpixelating Cameras Thayne Coffman EE381K-14 May 3, 2005

  2. Review – Motivation and Objective • Superpixellating (“VASI”) cameras • Translation of desired resolution to control signal can be done by halftoning • Which halftoning method will give the best ATR performance? • Block error diffusion • Blue noise dithering • Floyd & Steinberg error diffusion • Raster scan • Serpentine scan • Classical screening • 9-level clustered dot • 9-level dispersed dot • White noise • A method of my own design • vasiHalftone, vasiHalftone2 • Not exactly halftoning algorithms [McCarley et al, 2004] • Performance measured by • PSNR • WSNR • LDM (not a useful differentiator) • UQI

  3. Nontrivial Translation of Control Signal • Control signal vs. realized bandwidth • Nontrivial relationship caused by the geometry of pixel sharing patterns • Requires customization (inverse function) of control signal for each halftoning method • Stairstep patterns limit your control over actual realized bandwidth • Details in paper

  4. My Custom Methods – vasiHalftone, vasiHalftone2 • Semi-regularly spaced rectangles, size depends on desired bandwidth • For a given control signal • Consistently superior PSNR & WSNR • Consistently overshot desired bandwidth by ~30-100% • They were essentially cheating by using extra bandwidth • As currently designed, these methods have very poor bandwidth control Original Sharing Signal Resulting Image PSNR = 13.3 dB WSNR = 16.9 dB Desired BW = 9.6% Actual BW = 18.8% Inflation = 97%

  5. F&S Error Diffusion • Good performance and good bandwidth control • Good SNR in ROIs means accurate ATR • Good SNR in non-ROIs means good target acquisition • Good bandwidth control means precise VASI frame rate control Original Sharing Signal Resulting Image Desired BW = 11.6% Actual BW = 12.1% Inflation = 4% PSNR = 17.5 dB (33.3 dB in ROI) WSNR = 16.4 dB (33.8 dB in ROI)

  6. The Rest Original Block error diffusion Blue noise Original Clustered dot Dispersed dot White noise

  7. Conclusions • Floyd & Steinberg error diffusion gives the best results while still being able to control bandwidth precisely • vasiHalftone & vasiHalftone2 • Consistently the best PSNR, WSNR • Poor bandwidth control – overshot specifications by 30-100% • Bandwidth inflation means it’s not a fair comparison (they’re cheating) • Stochastic methods (white & blue noise) perform poorly • Outperformed by deterministic approaches • Susceptible to “catastrophic gray-out” • Classical screening performs marginally andhas bad bandwidth control

  8. References • P. McCarley, M. Massie, J.P. Curzan, “Large format variable spatial acuity superpixel imaging: visible and infrared systems applications,” Proc. SPIE, Infrared Technology and Applications XXX[sic.], vol. 5406, pp. 361-369, Aug 2004. • V. Monga, N. Damera-Venkata, B. Evans, Halftoning Toolbox for Matlab. Version 1.1 released November 7, 2002. Available online at http://www.ece.utexas.edu/~bevans/projects/halftoning/.

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