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cepheid

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You probably already know that any 1D signal that is a function of time (t) can be represented as a sum of sines and cosines (Fourier decomposition), each of which has a frequency measured in 1/s (or Hz). This

Similarly, any

So, after doing a DFT, the horizontal and vertical coordinate values in the transformed image represent horizontal and vertical spatial frequency axes. So the (0,0) point is the power contained in zero spatial frequency i.e. a constant level. For this reason, this component of the DFT is sometimes called the "DC level" of the image. You can increase or decrease the overall brightness of the image just by changing the value of the DC level ( the value at (0,0) ) of the DFT.

If you have an image with vertical stripes, you can consider this to be a sine wave oriented in the horizontal direction. In other words, your image only has ONE spatial frequency component, and it is the frequency of the sine wave (which is the inverse of the distance between white stripes or black stripes). If your stripes are spaced at 2 cm apart, then your spatial frequency will be (1 / 2 cm) = 0.5 cm

The reason why there would be points at both +0.5 and -0.5 is because with an FT you're actually decomposing your image into complex exponentials, rather than sinusoids. As a result, you have both positive and negative spatial frequencies.

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For more detailed image processing info, check this image sdk site....

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