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Biophotonics lecture 9. November 2011. Last time (Monday 7. November). Review of Fourier Transforms (will be repeated in part today) Contrast enhancing techniques in microscopy Brightfield microscopy Darkfield microscopy Phase Constrast Microscopy Polarisation Contrast Microscopy
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Last time (Monday 7. November) • Review of Fourier Transforms (will be repeated in part today) • Contrast enhancing techniques in microscopy • Brightfield microscopy • Darkfield microscopy • Phase Constrast Microscopy • Polarisation Contrast Microscopy • Differential Interference Contrast (DIC) Microscopy
Today • Part 1: Review of Fourier Transforms • 1D, 2D • Fourier filtering • Fourier transforms in microscopy: ATF, ASF, PSF, OTF • Part 2: Sampling theory
Fourier-transformation • Plane Waves are simple points in reciprocal space • A lens performs a Fourier-transformbetween its Foci Fourier-transformation & Optics
f f f f Laser Object Fourier-plane Image Fourier-transformation & Optics
imaginary b i = -1 A real a -1 1 The Complex Plane
Wavenumber: k [waves / m] imaginary real x x The Complex Wave
Excurse: Spatial Frequencies Real space: Frequency space: Intensity x [m] Amplitude k [1/m]
from:http://www-groups.dcs.st-and.ac.uk/ ~history/PictDisplay/Fourier.html Even better approximation: from:http://members.nbci.com/imehlmir/ Fourier Analysis
real imag. k k0 Examples real imag. x
Non-Periodic Examples (rect) real real x k
real k Non-Periodic Examples (triang) real x
real k Examples (comb function) real x Inverse Scaling Law !
real imag. -k0 k0 Examples real x k
Function is Self-Adjunct: Real Space Fourier Space Theorems (Real Valued) Functionis Real Valued
Real Space Fourier Space Theorems (Real + Symmetric) Function is Real Valued & Symmetric Function is Real Valued & Symmetric
Multiplication witha „spiral“ Real Space Fourier Space Theorems (Shifting) shift by Dx
Convolution Real Space Fourier Space Theorems Multiplication
Inverse scaling 1/a Real Space Fourier Space Theorems (Scaling) scaling by a
ky ky kx kx Constructing images from waves CorrespondingSine-Wave SpatialFrequency AccumulatedFrequencies SumofWaves
Constructing images from waves CorrespondingSine-Wave SpatialFrequency AccumulatedFrequencies SumofWaves
f f f f Laser Object Fourier-plane Image Fourier-transformation & Optics Low Pass Filter
f f f f Laser Object Fourier-plane Image Fourier-transformation & Optics High Pass Filter
Real Space (PSF) Reciprocal Space (ATF) Lens Cover Glass ky y x kx Focus z kz Oil Intensity in Focus (PSF)
McCutchen generalised aperture Ewald sphere
IFT Amplitude indicated by brightness Phase indicated by color
Amplitude Intensity
Point spread function (PSF) • The image generated by a single pointsource in the sample. • A sample consisting of many points hasto be “repainted” using the PSF as abrush. • Convolution ! • Image = Sample PSF • FT(Image) = FT(Sample) * FT(PSF)
IFT |.|2 square ? ? FT
Intensity in Focus (PSF), Epifluorescent PSF Fourier Transform ~ * ~ ~ I(k) = A(k) A(-k) OTF CTF I(x) = |A(x)|2 = A(x) · A(x)* ?
Region of Support kx,y kz Convolution: Drawing with a Brush
kx,y kz Optical Transfer Function (OTF)
2nsin(a)/l n sin(a)/l n/l kx,y kx,y a = kz kz n (1-cos(a))/l n (1-cos(a))/ l Widefield OTF support
Top view Missing cone
Image = Sample PSF FT(Image) = FT(Sample) * FT(PSF) contrast ky Optical Transfer Function 1 |kx,y| kx 0 |kx,y| [1/m] Cut-off limit A microscope is a Fourier-filter!
kz kz ky kx kx 1 kx Image = Sample PSF FT(Image) = FT(Sample) * FT(PSF) Real space Fourier domain Fourier domain Fourier Filtering suppresshigh spatialfrequencies DFT 0