430 Chapter 7. Position Sensitive Detection and Imaging
Image
Multiplication
Spike Function Sampled Data
Frequency Spectrum Spike Function
Convolution
Convoluted Spectrum
Convoluted Spectrum Box Function Reconstructed Spectrum
Multiplication
Convolution
Frequency Spectrum Spike Function Convoluted Spectrum
Convoluted Spectrum Box Function
Multiplication
Reconstructed Spectrum
(d)
(c)
(b)
(a)
(e)
Aliasing
Overlap
Overlap
Transformation
Fourier
Figure 7.1.5: (a) Sampling in spatial domain is equivalent to multiplication of the
image by a spike function. (b) Sampling in frequency domain is equivalent to con-
volution of the frequency spectrum with a spike function. (c) Multiplication of the
convoluted frequency spectrum by a sinc function leads to reconstruction of the
original frequency spectrum provided the sampling condition has been satisfied. (d)
Convolution of the frequency spectrum with spike function leading to sampling at a
frequency lower than the Nyquist frequency. The resulting copies of the frequency
spectrum overlap at the two ends. (e) Multiplication of the frequency spectrum
obtained in the last step with a box function to determine the original frequency
spectrum leads to aliasing.
The above examples clearly demonstrate the importance of Nyquist condition
(fs≥NNyq) in image sampling and reconstruction. However, even though this is a
necessary condition but is in no way the sufficient condition for producing an image