Digital Holography and Digital Image Processing: Principles, by Leonid Yaroslavsky

By Leonid Yaroslavsky

Electronic holography and electronic snapshot processing are twins born by way of laptop period. They proportion starting place, theoretical base, equipment and algorithms. the current publication describes those universal basics rules, equipment and algorithms together with picture and hologram digitization, info compression, electronic transforms and effective computational algorithms, statistical and Monte-Carlo tools, picture recovery and enhancement, picture reconstruction in tomography and electronic holography, discrete sign resampling and snapshot geometrical adjustments, exact measurements and trustworthy aim localization in photographs, recording and reconstruction of laptop generated holograms, adaptive and nonlinear filters for sensor sign perfecting and picture recovery and enhancement. The booklet combines thought, seriously illustrated useful equipment and effective computational algorithms and is written for senior-level undergraduate and graduate scholars, researchers and engineers in optics, photonics, opto-electronics and digital engineering.

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They define a vector-column a = {a k }. 18) for arbitrary coefficients vector: {A. r '# o} as a basis for representing any signal N-t aN = LCIr

In particular, 2-D separable eosine transform a Vx' fy)= fo fa(x, Y)cos(21tfxx )cos{21t/yY ~JY . 25) 2. Optical signals and transforms 45 Fig. 2-15 illustrates 2 types of symmetry that correspond to inseparable (left image) and separable (right image) integral eosine transforms. Figure 2-15. Two types of image even symmetry observed in images reconstructed from computer generated Fourier holograms. An important characteristic properties of integral eosine transform is that it has areal valued kerne!.

X)}tt= -oe fa (f)exp(- i21t (flr . X}tr. 12) Changing variables Rot_s . 14) Therefore if Fourier spectrum of a(x) is a (f), spectrum of a{Rots . f). Scaling theorem: Scaling signal coordinates S times causes I/S scaling ofits spectrum magnitude and spectrum coordinates. Proof oe

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