Download Advances in Electronics and Electron Physics, Vol. 67 by Peter W. Hawkes (ed.) PDF

By Peter W. Hawkes (ed.)

This quantity includes assessment articles masking a vast variety of subject matters in picture processing and research. the themes coated comprise snapshot research - which has united and harmonized a bunch of heterogeneous fabric; modern methods to the Fourier rework; quantity theoretic transforms, that are fairly beautiful for discrete, finite signs; using the Wigner distribution - which encodes either spatial and spectral details, for picture filtering; and purposes of the concept that of data strength. those updated surveys are meant to supply the reader with entry to the newest leads to the super lively box of picture technological know-how.

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Extra resources for Advances in Electronics and Electron Physics, Vol. 67

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9a, when the data are the ordinary and in-line structure factors of [ F,(u, u)[,as defined by Eq. 25, respectively, where the angular brackets denote an average over visibility space. The noise was independent between structure factors and was uniformly distributed between its extreme negative and positive values. , those far from the origin of visibility space) of F(u,u) are comparatively small, their signal-to-noise ratios are effectively lower. In fact, many of these signal-to-noise ratios are significantly less than unity, so that the visibility intensities corresponding to Figs.

Since positivity is clearly so important for practical phase retrieval, we summarize in Table 111 those physical situations in which positive images occur. IV. ITERATIVEPHASEREFINEMENT Having dealt with the preliminaries, we are now in a position to illustrate the power of existing phase retrieval algorithms. This section is concerned with the iterative procedures that form the core of all presently devised schemes for generating numerical solutions to Fourier phase problems. The ordinary and in-between samples (refer to Table 11) of the visibility constitute its pixels.

A suitable stopping criterion is to assume that f(x, y) is as close as can be expected to the true image-form when

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