Timeline for What is Lanczos resampling useful for in a spatial context?
Current License: CC BY-SA 3.0
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| Sep 2, 2011 at 15:41 | history | edited | johanvdw | CC BY-SA 3.0 |
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| Sep 2, 2011 at 15:29 | comment | added | johanvdw | I've integrated your comments. But within the cell, the smooth interpolator would most likely yield a better prediction | |
| Sep 2, 2011 at 15:28 | history | edited | johanvdw | CC BY-SA 3.0 |
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| Sep 2, 2011 at 15:22 | history | edited | johanvdw | CC BY-SA 3.0 |
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| Sep 2, 2011 at 14:58 | comment | added | whuber | I don't think these images are what you claim. The top right clearly is not the cell mean; if it were, the vertical stripes in its upper left quadrant wouldn't be there. Some form of "sharpening" was applied to that image to get the one beneath it (lower right), which is falsely aliased: this is not preservation of features, but creation of artifacts. Because (almost) all filters are unit normalized, including Lanczos filters, your point about the mean applies to every one of them, not just an unweighted neighborhood mean, and therefore is not a distinguishing characteristic. | |
| Sep 2, 2011 at 12:35 | history | answered | johanvdw | CC BY-SA 3.0 |