Illnab1024: The dark values in the spectrogram correspond to a low-amplitude coefficient in a frequency-domain representation of a certain block (maybe window?) of the original (time-domain) signal. Precise reconstruction of the waveform requires all of the coefficients. If those values aren't explicitly defined, we might implicitly assume that they're zero... but that would be rather similar to an
ubiquitous form of lossless compression 
Rick: Thanks for the tip! The BlendColorsWFP method is close to what I'm looking for.
barkbark00: You've identified a very important issue here: how can we run a filter on points near the boundary of the defined portion of a signal which isn't defined everywhere? My Eigen Blur effect essentially makes up values beyond the edge of the image. I treat the image as a periodic function and continue it a little ways past the bounds so that I can keep the filter
well-behaved. Apparently this is a common thing to do. Some other effects that I've seen assume that those values are zero or use a nearby value from the image. Some avoid handling pixels near the boundary altogether. Others modify the filter near the edges to avoid having to make up values, as you propose. It's hard to read, but I think that Rick's Gaussian Blur does this. Each of these different approaches probably makes sense in at least one interpretation
Edit: Found a better link for link #2.
Login
Register
FAQ
Search
