I’m reading a paper that talks about using a lerp function in image synthesis. What exactly is a lerp and how would you synthesize an image using one if you are given two images as inputs?
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I’m reading a paper that talks about using a lerp function in image synthesis. What exactly is a lerp and how would you synthesize an image using one if you are given two images as inputs?
‘lerp’ing is just a way to guestimate an intermediary value. For example, if one value was 10, and the next was 8, a ‘lerp’ function might return 9. There’s several ways to make the estimation – linear, trigonomic, etc. At its simplest, linear, you’re just taking
(distance from value 1 * value 1) + (distance from value 2 * value 2)where distance ranges from 0 to 1.In image processing, this is done with the color values between pixels. If you are zooming in past 100%, for example, you’d use a lerp function to determine what to draw in the areas that represent partial pixels.
I should add, I looked at that article, and it references Perlin noise. In that type of algorithm, lerp’ing functions are used quite extensively to calculate values in between points where data exists that can be passed into the perlin or fractal algoritm to generate a value for that intermediary point.