Wavefront Coding

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Summary• The role of Computational imaging• Hybrid imaging (wavefront coding)• The quid pro quo• Noise• Artefacts• Optimisation• Assuming artefacts can be removed• Artefacts• Origin and removal• Example optimization applications• Thermal infrared singlet• Ultra-miniature single-moving element zoom• Other computational imaging2
Why computational imaging?• Imaging optics are imperfect• Aberrations• Aliasing and detector space-bandwidth product• Reducing imperfection costs• Complexity• £• Volume• Weight• Logistics• All modern imaging systems involve optics and computation• Combined design and optimisation can enhance trade off and offernew capabilities• Diffraction-limited imaging through aberrations/conformal optics• Imaging in 4π steradians• Lensless imaging….3
Page 1: Computational Imaging:More pixels,
Page 5 and 6: Hybrid imaging5
Page 7 and 8: The additional parameter space with
Page 9 and 10: Effect of defocus when usingsymmetr
Page 11 and 12: Optimisation of artefact-free imagi
Page 13 and 14: Through-focus imaging fidelity13
Page 15 and 16: Expected imaging error• errorε 2
Page 17 and 18: Relative performance of cubic, pure
Page 19 and 20: Optimum phase amplitudeα optimum
Page 21 and 22: Artefacts⎡OH o'(x, y) = I −1 W2
Page 23 and 24: Decomposition of OTF• Defocus:•
Page 25 and 26: The origin of image replicationsOTF
Page 27 and 28: Parametric blind-deconvolution:Calc
Page 29 and 30: Accuracy of optical W 20DError in W
Page 31 and 32: Simplification of LWIR F/1 f=75mm G
Page 33 and 34: Pure and Generalised Cubic Solution
Page 35 and 36: IR singlet and phase maskDesignManu
Page 37 and 38: And as a movie37
Page 39 and 40: Single-moving-element zoom lenses:t
Page 41 and 42: No Phase maskGeneralised CubicPure

Wavefront Coding

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