Digital Holography and Wavefront Sensing: Principles, by Ulf Schnars, Claas Falldorf, John Watson, Werner Jüptner

By Ulf Schnars, Claas Falldorf, John Watson, Werner Jüptner

This ebook offers a self-contained therapy of the foundations and significant functions of electronic hologram recording and numerical reconstruction (Digital Holography). This moment version has been considerably revised and enlarged. The authors have prolonged the bankruptcy on electronic Holographic Microscopy to include new sections on particle sizing, particle photo velocimetry and underwater holography. a brand new bankruptcy now offers comprehensively and widely with computational wave box sensing. those suggestions symbolize a desirable substitute to straightforward interferometry and electronic Holography. they permit wave box sensing with out the requirement of a selected reference wave, hence permitting using low brilliance mild resources or even liquid-crystal monitors (LCD) for interferometric applications.

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Extra info for Digital Holography and Wavefront Sensing: Principles, Techniques and Applications

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This means the various unwrapping algorithm developed for HI and other methods can be used also for Digital Holographic Interferometry, because this technique also generates modulo 2π-images (see Chap. 4). 1 General Principles The concept of digital holographic recording is illustrated in Fig. 1a [196, 198]. g. Charged Coupled Device, CCD, or Complementary Metal Oxide Semiconductor, CMOS). The resulting hologram is electronically recorded and stored in a computer. The object is, in general, a three dimensional body with diffusely reflecting surfaces, located at a distance d from the sensor (measured to some representative plane).

The average intensity of all pixels of the hologram matrix is Im ¼ N À1 X N À1 1 X I ðkDx; lDyÞ N 2 k¼0 l¼0 ð3:43Þ The term a2R þ a2O can now be suppressed by subtracting this average intensity Im from the hologram: I 0 ðkDx; lDyÞ ¼ I ðkDx; lDyÞ À Im ðkDx; lDyÞ ð3:44Þ for k ¼ 0; . ; N À 1; l ¼ 0; . ; N À 1. The reconstruction of I 0 creates an image with strongly suppressed DC term. An example of this is shown in Fig. 12. The upper left figure is a photograph of the object. Reconstruction without DC term suppression is depicted in the upper right figure.

The superposition integral can be regarded therefore as a convolution and the convolution theorem (Annex A) can be applied. According to this approach the Fourier transform of the convolution of h Á ERÃ with È É g is the product of the individual transforms = hERÃ and =fgg. So Cðn; gÞ can be calculated by, firstly Fourier transforming h Á ERÃ , followed by multiplication with the Fourier transform of g, and, finally, taking an inverse Fourier transform of the product. Three Fourier transforms are therefore necessary to complete the whole process.

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