Re:

Hi Michel,
Let me suggest that you are thinking about this problem in a fundamentally
wrong way. You have image 1, and want to create image 2 that is a
different size. Further, you want image 2 to be similar to image 1 â??in
some sense.â?? In other words, the two images cannot be identical, so
you need to define a criterion for measuring the â??correctnessâ?? of
image 2. The method you are trying (frequency band filtering with
decimation/interpolation) achieves this â??in the senseâ?? that the two
images have similar frequency spectra.

Hereâ??s the catch. The information you are dealing with is encoded in
the spatial domain, not the frequency domain. That is, you are interested
in the spatial patterns, their edges, their positions, their amplitudes,
and so on. Accordingly, you want image 2 to be similar to image 1 in
â??some senseâ?? that is related to the spatial domain. This is in
contrast to, for example, an audio signal that is primarily encoded in the
frequency domain.

The problems you are seeing are a direct result of trying to manipulate
the data in the wrong domain. For instance, when you perform simple
filtering in the frequency domain, you create unpredictable artifacts in
the spatial domain. Instead, ask yourself this, â??how should a pixel in
image 1 affect each pixel in image 2?â?? For instance, should an isolated
bright pixel in the original image be converted to a single bright pixel in
the new image?

Hope this helps.
Regards,
Steve
Steve.Smith1@xxxxxxxxxxxxxxx
.

Relevant Pages

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