Image processing

Chikawa, J.

doi:10.1107/97809553602060000604

International
Tables for
Crystallography
Volume C
Mathematical, physical and chemical tables
Edited by E. Prince

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International Tables for Crystallography (2006). Vol. C. ch. 7.1, p. 635

Section 7.1.7.3. Image processing

J. Chikawa^c

7.1.7.3. Image processing

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The resolution δ and integration time t should be selected appropriately according to experimental requirements (Chikawa, 1980). For example, when topographic images of a single dislocation in silicon were observed with t = 1/30 s by synchrotron radiation, their contrast and SNR were found to be C = 0.5 and R_I = 20 for δ = 30 µm, and C = 1 and R_I = 8 for δ = 6 µm. Since the SNR is desired to be 100, the integration time should be as large as possible unless images of moving objects are degraded. Digital image processing (Heynes, 1977) enables one to adjust the integration time easily. As an example, a noise reducer (McMann, Kreinik, Moore, Kaiser & Rossi, 1978; Rossi, 1978) is shown in Fig. 7.1.7.4. The video signal is sampled and digitized by the A/D converter and the digital video is sent to the adder and thence to the memory. Image information in the memory is continually sent both to the adder through the multiplier for combination with incoming data and to the display through the D/A converter. The weighting of new to old data is made by changing the factor k of the multiplier in the range $[0\le k\le1]$ . For k = 0, the original input image is displayed. In the range $[0\lt k\lt1]$ , a sliding summation of successive frames is displayed, and the SNR is improved by a factor of $[[(1+k)/(1-k)]^{1/2}]$ . The factor k can be adjusted automatically by detecting the difference between successive frames.

Figure 7.1.7.4| top | pdf |

Principles of a noise reducer.

Using a HARP tube, the SNR can be improved without integration of the amplifier noise by image processing, and topographs were displayed with an intensity of $[\nu_p\simeq]$ [10^9] photons s⁻¹ m⁻² by a conventional X-ray generator.

Acquisition of extremely low intensity images, dramatic improvements in SNR via frame integration, and isolation and enhancement of selected-contrast ranges are possible by digital image processing (Chikawa & Kuriyama, 1991).

References

Chikawa, J. (1980). Laboratory techniques for transmission X-ray topography. Characterization of crystal growth defects by X-ray methods, edited by B. K. Tanner & D. K. Bowen, Chap. 15, pp. 368–400. New York: Plenum.Google Scholar

Chikawa, J. & Kuriyama, M. (1991). Topography. Handbook on synchrotron radiation, Vol. 3, edited by G. Brown & D. E. Moncton, Chap. 10, pp. 337–378. Amsterdam: Elsevier.Google Scholar

Heynes, G. D. (1977). Digital television; a glossary and bibliography. SMPTE J. 86, 6–9.Google Scholar

McMann, R. H., Kreinik, S., Moore, J. K., Kaiser, A. & Rossi, J. (1978). A digital noise reducer for encoded NTSC signals. SMPTE J. 87, 129–133.Google Scholar

Rossi, J. P. (1978). Digital technique for reducing television noise. SMPTE J. 87, 134–140.Google Scholar

International Tables for Crystallography (2006). Vol. C. ch. 7.1, p. 635