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THz Signal & Image Processing

THz Signal & Image Processing. Outline. SECTION 1: Alternative configurations Wide beam configuration (synthetic aperture processing) Tomographic configuration ( tomosynthesis processing) SECTION 2: Challenge of data size Enhanced visualisation (Semi-) Automatic defect detection.

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THz Signal & Image Processing

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  1. THz Signal & Image Processing

  2. Outline • SECTION 1: Alternative configurations • Wide beam configuration (synthetic aperture processing) • Tomographic configuration (tomosynthesis processing) • SECTION 2: Challenge of data size • Enhanced visualisation • (Semi-) Automatic defect detection

  3. Outline • SECTION 1: Alternative configurations • Wide beam configuration (synthetic aperture processing) • Tomographic configuration (tomosynthesis processing) • SECTION 2: Challenge of data amount • Enhanced visualisation • (Semi-) Automatic defect detection

  4. Wide beam configuration in-depth defects Beam waist depth Top / overhead view depth Top / overhead view material under test material under test focused beam lenses unfocused beam unfocused beam THz THz THz THz THz THz THz THz azimuth azimuth Synthetic Aperture (SA) FMCW Focused FMCW • Small focused beam • Diffraction-limited • Data already focused • Lateral resolution: 1-3 mm • No lenses needed • Wide unfocused beam (16º) • Data is focused in software • Lateral resolution: 4-7 mm

  5. 3-D synthetic aperture imagery Inserts - A-sandwich Rohacell core Honeycomb core Near surface 100 GHz – Side A

  6. 3-D synthetic aperture imagery Debonds - A-sandwich - honeycomb core Near surface 100 GHz – Side A In depth

  7. 3-D synthetic aperture imagery Debonds - A-sandwich - Rohacell core 100 GHz – Side B Near surface 150 GHz – Side B Near surface

  8. 3-D synthetic aperture imagery Debonds - C-sandwich - honeycomb core 100 GHz – Side B Near surface 150 GHz – Side B

  9. 3-D synthetic aperture imagery Impact (30 J) - Solid laminate - fibre glass 100 GHz – Side A 100 GHz – Side B Near surface

  10. Tomographic configuration Tomosynthesis in transmission mode Data procedure for 3-D imaging • Technique for structural reproduction of object • In THz the beam is close to a Gaussian distribution • Information from reflected or transmitted beam Process of acquisition/reconstruction • Acquisition composed of a set of projections • Modeled by the Radon transform

  11. Tomographic configuration Tomosynthesis in reflection mode View B View C View A • Reconstruction of internal structure with more accuracythan unique reflectionimage • Allow to converge to diffraction limit for BOTHlateral and longitudinal resolution

  12. Tomosynthesis Inserts – Solid laminate – Glass fibre 100 GHz – Side A Images at different depths

  13. Outline • SECTION 1: Alternative configurations • Wide beam configuration (synthetic aperture processing) • Tomographic configuration (tomosynthesis processing) • SECTION 2: Challenge of data size • Enhanced visualisation • (Semi-) Automatic defect detection

  14. Challenge of data size FMCW system 3-D data set – spatial information TDS 3-D data set – spatial information 3-D data set – frequency information CHALLENGE FOR THE OPERATOR • DOTNAC • Enhanced visualisation for flat and curved samples • (Semi-) Automatic defect detection

  15. Defect visualisation Water inclusion- A-sandwich - Honeycomb core Raw image representation Processed image representation

  16. Defect visualisation Impact (30 J) - Solid laminate - fibre glass

  17. Automatic defect detection Inserts - Solid laminate - fibre glass

  18. Automatic defect detection Inserts - Solid laminate - fibre glass

  19. 3-D Visualisation In-situ test on radome Imaging with FMCW system 1 screenshot 3-D In-depth viewing

  20. Questions?

  21. Questions?

  22. Reconstruction methods: BFP BFP: Backprojection of Filtered Projections W0 corresponds to the projection P filtered by a ramp filter to increase details A is the weight coefficient between the projection (θ;ρ) and the pixel (i; j) We sum the filtered projections crossing each point March 6th 2012

  23. Iterative methods • Makeinitiakguess • Check how wellit corresponds to the measured data • Calculate the differencebetween the result and real measurement • Correct the values • Repeatuntilresultssatisfying • SART: SimultaneousAlgebraic Reconstruction Technique • OSEM (Ordered Subsets Expectation Method)

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