Legacy ImageMagick Discussions Archive

you may be able to accomplish what you want using a wavelength-selective filter in front of your lense.

-h

How to make colorspace support generic? Well, that's a problem! The generic answer is: - N channels - Each channel has a specific spectral power curve and power baseline. - Each channel has a specific luminance curve Y=f(X). This makes it possible to represent any input device (raw sensor, or ...

Whenever I see such amazing examples, I am struck by sceptisism: 1. Is the image degraded by a real, relevant blurring (such as out of phocus lense, camera movement), or by a synthetic degradation that satisfy some ideal property (such as space-invariance, noise-free etc) 2. How much manual work is ...

Note that while the filter function used may be the same for a 1000 -> 1001 resize as for a 1000 -> 1002 resize, the actual samples or weights generated by the function will vary. That is because the actual distance of actual source pixels (weighted values) from the sample point (reversed mapped ...

... There is a BBC whitepaper that suggests that image resolution can be somewhat reduced if the reconstruction filter is "sharp". I.e. applying sharpening after upsampling an image, you can perceptually achieve the same thing as actually having somewhat higher resolution. This may not surprise you ...

... I have not pondered much about the general, complex distorted case. Would it be possible to assume "local uniformity" over a suitable neighbourhood of pixels, calculate a local spatial cutoff frequency (either rotationally symmetric or tensor), and design a local kernel tailored for the local ...

I thought that "bilinear" as a term was used for 2-d triangular filtering where the triangle is scaled so that a maximum of 4 input pixels contributed to one output pixel. If that is your definition as well, then I would be very sceptical about bilinear filtering for downscaling by large factors ...

If we had an accurate model of the HVS that could be turned into a "score", we could, at least in principle, select a large class of matrices (and a class of color space transformations, because, really, with sRGB, for example, there already is nonlinearity introduced into the system) that would ...

What complicates things is that if you change the geometrical operation, you change the matrix completely, and then, in a sense, you must extract a recipe or pattern from a collection of (parameterized?) matrices based on a score that does not match what humans want very well. I have not pondered ...

Here is an example of complications: bilinear (Triangle, in IM) is actually a decent scheme when you enlarge "a little", or when you downsample. It's horrid if you enlarge a lot. I thought that "bilinear" as a term was used for 2-d triangular filtering where the triangle is scaled so that a maximum ...

As the documentation explains, any "linear" resampling is a subset of out(i,j) = sum(in * Mij), where Mij is an array the size of the input image that changes values for every output pixel (might be seen as 4-d). Finding the visually most appealing and/or most accurate linear scaling should reduce ...

Anti-aliasing quality can be better with EWA (elliptical/circular) filters, especially if not a simple constant scaling. See perspective transformations at http://www.imagemagick.org/Usage/distorts/#horizon. The elliptical filters can do a better job of "averaging" pixels over a spread out region ...

I consider theory to be a tool to understand and formulate better approaches. No more and no less. The pudding always is king. If you want to make pudding, only the pudding matters, not the fancy theories used to make it. I guess that I dont see the same conflict between practice and theory that ...

Short answer... Speed. It is a lot faster to resize images in two passes using 1-d filters, than to resize in 1 -pass using 2-D filters. It can in fact be an order of magnitude faster. This is also why Blur's are implemented using 2-pass 1-dimensional Gaussian, than 1-pass 2-dimensional Gaussian ...

...My instinct is to maximize the information that can be recorded/reconstructed error-free... Let's start with enlarging. If your goal is to maximize the information that can be reconstructed error free, simply enlarge with nearest neighbour (convert {input} -filter Point -resize {width}x{height ...