2D dual via 1D dual

Yesterday I finally wrote a routine which computes a non-separable (dilated and rotated) 2D Gaussian. It takes parameters for horizontal and vertical dilation of the 2D Gaussian which is then rotated by a corresponding parameter. If it is neither dilated nor rotated, it is numerically identical to the pure 2D Gaussian. It has N. Kaiblinger’s gaussnk.m as background when it is computed on an area which is 7 times as large as the desired signal length but then wrapped (summed up) into the smaller region. I won’t publish it yet, as it can be done better; currently I separated the tasks of computing and wrapping, but they could be done at once.

With this I could finally reproduce a graphic from the paper “2D-GA Based on 1D Algorithms”: It shows (1) a non-separable 2D atom with relatively prime height and width, (2) the atom mapped to vector shape, (3) the dual of that vector with regard to some combined time and frequency steps, and (4) the dual vector reshaped to an image.

The question remains about how to finally do GA using these two 2D atoms. The only ways I found so far was either building the 1D Gabor system (of the atom shaped as vector) or computing a sampled STFT by that 1D vector; this works because modulations stay modulations. However, in the case of separable 2D atoms, this can be done in another way, as I’ll show in another article.

Posted by Stephan Paukner in Master's Thesis at 11:14 | Comments (0) | Trackback (1)

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Logbook of Stephan Paukner on : Dilated + rotated 2D Gaussian

I&#8217;ve finally improved my script that computes a dilated and rotated 2D Gaussian with respect to low memory consumption. It applies a dilation and rotation matrix to the 2D domain. I published it under the GNU GPL v2, so if you find any improvements,

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