🚀 go-pugleaf

In article <1d3ji1INN759@cs.tut.fi>, defee@tukkasotka.tut.fi (Irek Defee) writes:
|> 
|> I would like to know present state-of-the-art in algorithms for
|> high-quality image z o o m i n g, especially for scaling-down, but
|> also for scaling up, by any factor. That is, how to diminish/enlarge an
|> image, with minimum perceptual quality loss, from (x1,y1) to (x2,y2) pixels?
|> This seems to be easy using photographic enlarger, but not so easy
|> in general with digital images. On the other hand, such things are 
|> running on computer displays.
|> 
|> Any info on (clever) algorithms, current implementations, references
|> and review material will be appreciated.
|> 
|> 
|> Irek Defee
|> Signal Processing Laboratory,
|> Tampere University of Technology,
|> Tampere, Finland.
|> Email: defee@cs.tut.fi
|> Fax: +358-31-161857
|> Voice: +358-31-162696


Scaling down is easy, just low-pass filter and decimate. Scaling up on computer
displays is usually done by just repeating pixels. Better results can be 
obtained by bilinear interpolation with some loss in resolution however. Good
results can be obtained by interpolation followed by a good (many taps) low-pass
filter. The fractal technique pioneered by Barnsley (see article by A. Jacquin,
IEEE Trans. Image Processing, Jan 1992) can give very pleasing effects when 
used for magnification.

-Ashok Rao (Comsat Laboratories)

In article <1d4bptINN7rr@elmer.ctd.comsat.com> rao@ctd.comsat.com (Ashok Rao) writes:
>In article <1d3ji1INN759@cs.tut.fi>, defee@tukkasotka.tut.fi (Irek Defee) writes:
>|> I would like to know present state-of-the-art in algorithms for
>|> high-quality image z o o m i n g, ...
>Scaling down is easy, just low-pass filter and decimate. 

I think it just seems to be easy since the linear approach would require in
fact complicated multirate conversion and decimation filters for each
zooming ratio. That would lead to blurring artifacts. 

However, there is even more intricacy in this problem. This can be
illustrated on the following example. Let's have an image which is
just a cosinusoid of certain (enough high) frequency. Using the
standard approach with lowpass filter and decimation, this cosinusoid
will be removed and the resulting image will be perceptually
unacceptable as a zoomed-down version of the original one. In this 
case, a better version wolud be a cosinusoid with frequency scaled to
the size of the new image.

>Scaling up on computer
>displays is usually done by just repeating pixels. Better results can be 
>obtained by bilinear interpolation with some loss in resolution however. Good
>results can be obtained by interpolation followed by a good (many taps) 
>low-pass filter. 

Here again blurring will result. Some nonlinear technique might be
better, as we don't need to interpolate e.g. step edges.

>-Ashok Rao (Comsat Laboratories)

Thanks,

Irek Defee

In article <1d3ji1INN759@cs.tut.fi> you write:
>
>I would like to know present state-of-the-art in algorithms for
>high-quality image z o o m i n g, especially for scaling-down, but
>also for scaling up, by any factor. That is, how to diminish/enlarge an
>image, with minimum perceptual quality loss, from (x1,y1) to (x2,y2) pixels?
>This seems to be easy using photographic enlarger, but not so easy
>in general with digital images. On the other hand, such things are 
>running on computer displays.
>
>Any info on (clever) algorithms, current implementations, references
>and review material will be appreciated.
>
>
>Irek Defee

There's been a series of image processing articles carried by the C
Users Journal starting from March 1991.  The current issue Nov.'92 covers image 
operations such as zooming, scaling, rotation, and others.  The article includes
complete C source code for manipulating TIFF images, but the alogrithms
can easily be converted to other formats.

Jason
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