Resampling has a bad name among many photographers. Here’s a typical pronouncement, from here: “I am not going to address resampling here because it degrades an image and has little application in fine art photography. (Resampling is when Photoshop adds pixels to an image.)” Dodgy grammar aside, I strongly disagree. On the artistic level, I… [Read More]
Output antialiasing
Let’s review conventional sampling theory. We start with a continuous representation (the real world, as imaged by the lens), filter that to remove spectral components above half the sampling frequency, sample at evenly spaced infinitesimal points, digitize the results, and store them. To reconstruct the input we take the samples, recreate their values and locations,… [Read More]
Diffraction, DOF, and digitization in ideal lenses
In response to some e-mail comments about my anti aliasing posts, I’ve been thinking about diffraction, and how it affects format selection. In order to clarify my thinking, I prepared the following spreadsheet: In the first column is the f/ stop. The second column is the horizontal or vertical pixel spacing in micrometers of a… [Read More]
Antialiasing – email comments
I’ve had some email on the antialiasing posts. One person quotes me from Antialiasing, part 2 as follows: The good news is that increasing the area of the sensor receptors reduces aliasing, and does it fairly efficiently. William Pratt, in his book Digital Image Processing, 2nd Edition, on pages 110 and 111, compares a square receptor… [Read More]
Antialiasing, part 4
Antialiasing the future It’s pretty clear to me that the biggest aliasing problems today are caused by the Bayer pattern and similar methods that construct a color sensor by detecting different spectra at different places on the chip. One way to make a big improvement would be to get all the RGB photosensitive regions that… [Read More]
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