Digital Holography and Digital Image Processing pp 275-312 | Cite as

# Statistical Computation Methods and Algorithms

Chapter

## Abstract

By definition, the distribution function is called the

**P****(****V****)**of a random variable*is the probability that the random variable does not exceed the value***v***. The derivative of***V****P****(****V****)**with respect to**V**$$
p\left( v \right) = {\left. {\frac{{dP\left( V \right)}}{{dV}}} \right|_{V = v}}
$$

*of the random variable v. Digital signals are characterized by discrete analogs of the distribution function and distribution density respectively — the relative share***probability distribution density****R****(****m****)**of the samples that do not exceed the given quantized value*, and the rate***q****h****(****q****)**of the samples having the value*. The latter characteristic is referred to as signal***q***,the former one as***distribution histogram***.***cumulative distribution histogram**## Keywords

Power Spectrum Impulse Noise Speckle Noise Digital Holography Speckle Contrast
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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## References

- 1.P. J. Huber, Robust Statistics, John Wiley and Sons, N.Y., 1981Google Scholar
- 2.W. H. Press, S. A. Teukolsky, W. T. Vetterling, B. P. Flannery, Numerical Receipes in C. The Art of Scientific Computing, Second Edition, Cambridge University Press, 1995Google Scholar
- 3.L. Yaroslaysky, M. Eden, Fundamentals of Digital Optics, Birkhauser, Boston, 1995Google Scholar
- 4.L. B. Lesern, P. M. Hirsch, J. A. Jordan, Kinoform, IBM Journ. Res. Dev., 13, 150, 1969Google Scholar
- 5.L. P. Yaroslayskii, N. S. Merzlyakov, Methods of Digital Holography, Consultant Bureau, N.Y., 1980Google Scholar
- 6.N. C. Gallagher, B. Liu, Method for Computing Kinoforms that Reduces Image Reconstruction Error, Applied Optics, v. 12, No. 10, Oct. 1973, p. 2328ADSCrossRefGoogle Scholar
- 7.Goodman, J.W.,. Statistical Properties of Laser Speckle Patterns In Laser Speckle and Related Phenomena, J.C. Dainty, ed. Springer Verlag, Berlin, 1975Google Scholar
- 8.L. Yaroslaysky, A. Shefler, Statistical characterization of speckle noise in coherent imaging systems, in: Optical Measurement Systems for Industrial Inspection III, SPIE’s Int. Symposium on Optical Metrology, 23–25 June 2003, Munich, Germany, W. Osten, K. Creath, M. Kujawinska, Eds., SPIE v. 5144, pp. 175–182Google Scholar

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© Springer Science+Business Media New York 2004