On the leftmost image, there’s no interpolation of data-the checkerboard is rendered in black and white pixels as it recedes back in perspective, and quickly becomes a mess. When we look at these computer rendered checkerboards, we can begin to understand what anti-aliasing is doing to improve and approximate images. Even the smartest math can’t create something from nothing. While it is more complicated that simple guessing-there are formulas and proper methods for Interpolation-it can’t be expected to be a perfectly accurate representation of the image data that is actually there. an educated guess on what might actually be in that spot if more data points were available. Interpolation: Creating Something From (Almost) Nothing?ĭigital photography is an approximation of the colors and values present when light hits a sensor-in this same way, anti-aliasing is an approximation of image data using a technique called “ Interpolation.” Interpolation is a fancy-pants math term meaning data created based on the trends of existing data, i.e. While this property of pixels and its use in photography is not anti-aliasing exactly, understanding this property of digital photography is one of the best places to start a solid understanding of what anti-aliasing is. Pixels are handy because high-resolution images can approximate colors and shapes, accurately recreating an image in a way that is similar to film-based photography. The stopping action (ability of the camera to create sharp images from moving objects) can never be perfect-at least it seems very, very unlikely. This means it may be absolutely impossible to get the absolute location of that single particle of light at the time it hit the sensor-photography is only an approximation of how that light is captured. It’s likely that even if we developed cameras capable of reading the locations of individual photons with quantum precision as they hit the sensor, because of the weird nature of physics at the quantum level, the individual particles may actually appear in multiple places on the sensor at the same time. That’s the problem with photography-light isn’t as precise as it would need to be to be captured in a perfectly mathematical way. Even if a monitor cannot render a line segment’s infinite thinness (it always has to show it in pixels), it still is as thin as a line existing only in a theoretical mathematical world. Because they are so absolute, there’s no blurring the line between where they are and where they are not.

Vectors are precise they exist at absolute coordinates on an algebraic grid. There are a number of fundamental differences between the two: pixels are ordered arrays of light, pigment, or color vectors are mathematical representations of lines, shapes, gradients, etc. You may remember an article from a year ago where we talked about the difference in Vectors and Pixels. Vectors and Pixels, and Why Cameras Take Pictures With Pixels

Minecraft anti aliasing is bad