3 ms·

Reeeaallly? I haven't made the images, but my intuition is telling me that text will be noticeably blurry compared with a box filter. I basically agree with yo

Reeeaallly? I haven't made the images, but my intuition is telling me that text will be noticeably blurry compared with a box filter. I basically agree with your points regarding compositing in a linear space, except that I suspect that thin black-on-white lines will come out looking thin and spindly.

BubRoss 7y ago
It sounds like you are talking about text that doesn't move. If you want a general filter that can give a result without visible aliasing while sacrificing as little sharpness as possible, a 2.2 gauss filter is very hard to beat and I have spent a lot of time trying. Box filters can be sharper, lancoz filters can be better for scaling down a final image, etc. but they will alias in a general sense. You might not see it in static text which is fine. Also thin black on white lines are an extreme outlier, since what you percieve is relative and the entire image matters. It is more into the realm of optical illusion that play off our relative sensitivity.
- raphlinus 7y ago
  So obviously text is one of the things I care about a lot. I'm willing to accept your filter as being very good for a lot of stuff other than presenting a GUI. Does this mean that there is not one true right answer for images, as there is for audio[0]? That you should use different reconstruction filters depending on the application. Is it accurate to say that a pixel is not a little square unless you're rendering text, in which case it is? [0] I know this is a slight oversimplification, if you care deeply about latency you might choose between linear and minimal phase, etc. But for consumer applications it's true enough.
- jacobolus 7y ago
  A Gaussian kernel will reduce ringing artifacts, but is much blurrier than alternative resampling kernels. https://www.imagemagick.org/Usage/filter/nicolas/ https://www.imagemagick.org/Usage/filter/nicolas/ Does “diameter” here mean “twice the standard deviation”?
  - BubRoss 7y ago
    No, diameter means the width of the filter in pixels. Each side would extend 1.1 pixels for a 2.2 diameter filter. If you compare filters at the same width, gauss will be softer, which is why you can lower the diameter.
    - jacobolus 7y ago
      A Gaussian filter has infinite support, and is characterized by its variance (or standard deviation). https://en.wikipedia.org/wiki/Gaussian_filter https://en.wikipedia.org/wiki/Gaussian_filter A ‘Gaussian’ which extends 1.1 units is a non-standard and not clearly defined thing. Are you picking some fraction of 1.1 as the standard deviation and truncating after? (Often Gaussian filters are truncated after 3 standard deviations, or similar.) Are you multiplying by some other window function? ... Can you link to a more explicit formal description of what you mean?
      - BubRoss 7y ago
        When I say 2.2 pixels as the diameter, I mean roughly that a pixel will be made up of all the samples 1.1 pixels or closer to the center of the pixel and they will be weighted by a gauss curve. How that gauss curve is actually used is not formal or strictly defined, but is usually a curve that goes out to about 3 standard deviation a baked into a LUT and normalized. A curve that uses more standard deviations would have to be wider in pixels to look similar.
        jacobolus 7y ago
        Do you have some code for what you specifically are talking about? Or a formal description? You have been saying here “this kernel is better than all of the alternatives” but it’s hard to evaluate that kind of claim without knowing precisely what you mean. “not formal or strictly defined” is not super encouraging.
        BubRoss 7y ago

BubRoss 7y ago

It sounds like you are talking about text that doesn't move. If you want a general filter that can give a result without visible aliasing while sacrificing as little sharpness as possible, a 2.2 gauss filter is very hard to beat and I have spent a lot of time trying. Box filters can be sharper, lancoz filters can be better for scaling down a final image, etc. but they will alias in a general sense. You might not see it in static text which is fine. Also thin black on white lines are an extreme outlier, since what you percieve is relative and the entire image matters. It is more into the realm of optical illusion that play off our relative sensitivity.

raphlinus 7y ago
So obviously text is one of the things I care about a lot. I'm willing to accept your filter as being very good for a lot of stuff other than presenting a GUI. Does this mean that there is not one true right answer for images, as there is for audio[0]? That you should use different reconstruction filters depending on the application. Is it accurate to say that a pixel is not a little square unless you're rendering text, in which case it is? [0] I know this is a slight oversimplification, if you care deeply about latency you might choose between linear and minimal phase, etc. But for consumer applications it's true enough.
jacobolus 7y ago
A Gaussian kernel will reduce ringing artifacts, but is much blurrier than alternative resampling kernels. https://www.imagemagick.org/Usage/filter/nicolas/ https://www.imagemagick.org/Usage/filter/nicolas/ Does “diameter” here mean “twice the standard deviation”?
- BubRoss 7y ago
  No, diameter means the width of the filter in pixels. Each side would extend 1.1 pixels for a 2.2 diameter filter. If you compare filters at the same width, gauss will be softer, which is why you can lower the diameter.
  - jacobolus 7y ago
    A Gaussian filter has infinite support, and is characterized by its variance (or standard deviation). https://en.wikipedia.org/wiki/Gaussian_filter https://en.wikipedia.org/wiki/Gaussian_filter A ‘Gaussian’ which extends 1.1 units is a non-standard and not clearly defined thing. Are you picking some fraction of 1.1 as the standard deviation and truncating after? (Often Gaussian filters are truncated after 3 standard deviations, or similar.) Are you multiplying by some other window function? ... Can you link to a more explicit formal description of what you mean?
    - BubRoss 7y ago
      When I say 2.2 pixels as the diameter, I mean roughly that a pixel will be made up of all the samples 1.1 pixels or closer to the center of the pixel and they will be weighted by a gauss curve. How that gauss curve is actually used is not formal or strictly defined, but is usually a curve that goes out to about 3 standard deviation a baked into a LUT and normalized. A curve that uses more standard deviations would have to be wider in pixels to look similar.
      - jacobolus 7y ago
        Do you have some code for what you specifically are talking about? Or a formal description? You have been saying here “this kernel is better than all of the alternatives” but it’s hard to evaluate that kind of claim without knowing precisely what you mean. “not formal or strictly defined” is not super encouraging.
        BubRoss 7y ago