If the FilterMode is currently Point, switch it to Trilinear on the Button click M_MyTexture.filterMode = FilterMode.Point If the FilterMode is currently Bilinear, switch it to Point on the Button click Switch the Filter Mode of the Texture when user clicks the Button Switch between Filter Modes when the user clicks the Button FilterMode SwitchFilterModes() Output the current Filter Mode to the consoleĭebug.Log("Filter mode : " + m_MyTexture.filterMode) M_MyTexture.filterMode = SwitchFilterModes() Press the space key to switch between Filter Modes Remember to assign a Texture in the Inspector window to ensure this works Apply the Texture to GameObjects (click and drag the Texture onto a GameObject in Editor mode) in your Scene to see it change modes in-game. Click on the GameObject and attach a Texture to the My Texture field in the Inspector. It switches between Point, Bilinear and Trilinear filter modes. However, I hope this answers your question "why sinc", and gives you some idea about frequency responses and so forth.//This script changes the filter mode of your Texture you attach when you press the space key in Play Mode. Also, for a=1 and 2, the frequency response does not look much like a step function.
#Modul8 preload bilinear filter vs lossless quality windows
There are a wide variety of windows available, which work just about as well.
Please note that there is no magic about any of this. the last two factors ("the window") also tone down the ringing they make a vast improvement in both the perceptual artifact and the practical incidence of "undershoot" - though without completely eliminating them.the sinc(pi x/a) smooths out the edges of the box and (consequently? equivalently?) greatly improves the rejection of undesirable high frequencies.the box(|x|the sinc(pi x) determines the overall shape of the frequency response (for larger a, the frequency response looks more and more like a box function).Specifically, this will get you something like the Lanczos filter: Lanczos filter: L(x) = sinc(pi x) sinc(pi x/a) box(|x| Since you are familiar with Fourier analysis for signal processing, you don't really need to know much more to apply it to image processing - all the filters of immediate interest are "separable", which basically means you can apply them independently in the x and y directions. That said, I will go ahead with some theory. There are a lot of good filters out there, and the choice between the best frequently comes down to a judgement call. The selection of a particular filter for image processing is something of a black art, because the main criterion for judging the result is subjective: in computer graphics, the ultimate question is almost always: "does it look good?".
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