ANISOTROPIC FILTERING

In 3D computer graphics, 'anisotropic filtering' (abbreviated 'AF') is a method of enhancing the image quality of textures on surfaces that are at oblique viewing angles with respect to the camera where the projection of the texture (not the polygon or other primitive it is rendered on) appears to be non orthogonal. Like bilinear and trilinear filtering it eliminates aliasing effects, but introduces less blur at extreme viewing angles and thus preserves more detail. Anisotropic filtering is relatively expensive (usually computationally, though the standard space-time tradeoff rules apply) and only became a standard feature of consumer-level graphics cards in the 1990s.

Contents

An Improvement on Isotropic MIP Mapping

Implementation

Performance & Optimization

See also

External links

An Improvement on Isotropic MIP Mapping

Hereafter, it is assumed the reader is familiar with MIP mapping.
If we were to explore a more approximate anisotropic algorithm, RIP mapping (rectim in parvo) as an extension from MIP mapping, we can understand how anisotropic filtering gains so much texture mapping quality. If we need to texture a horizontal plane which is at an oblique angle to the camera, traditional MIPmap minification would give us insufficient horizontal resolution due to the reduction of image frequency in the vertical axis. This is because in MIP mapping, each MIP level is isotropic, so a 256×256 texture is downsized to a 128×128 image then a 64x64 image and so on, so resolution halves on each axis simultaneously, so a MIP map texture probe to an image will always sample an image that is of equal frequency in each axis. Thus when sampling to avoid aliasing on a high frequency axis the other texture axes will be similarly downsampled, and therefore potentially blurred.
With RIP map anisotropic filtering, in addition to downsampling to 128x128 images are also sampled to 256x128 and 32x128 etc. These anisotropically downsampled images can be probed when the texture mapped image frequency is different for each texture axis and therefore one axis need not blur due to the screen frequency of another axis and aliasing is still avoided. RIP mapping has a limitation in that it only supports anisotropic probes that are axis aligned in texture space so diagonal anisotropy still presents a problem for example, and real use cases of anisotropic texture commonly have such screenspace mappings.

Implementation

True anisotropic filtering probes the texture anisotropically on the fly on a per-pixel basis for any orientation of anisotropy. In graphics hardware typically when the texture is sampled anisotropically, several probes (texel samples) of the texture around the center point are taken, but on a sample pattern mapped according to the projected shape of the texture at that pixel. Each probe is often in itself a filtered MIP map sample which adds more sampling to the process. Sixteen trilinear anisotropic samples might require 128 samples from the stored texture, as trilinear MIPmap filtering needs to take four samples times two MIP levels and then anisotropic sampling (at 16-tap) needs to take sixteen of these trilinear filtered samples.

Performance & Optimization

The sample count required can make anisotropic filtering extremely bandwidth intensive. Each sample could be four bytes or more so each anisotropic pixel could require 512 bytes from texture memory, although texture compression is commonly used to reduce this. A display can easily contain over a million pixels, so the hit on texture memory can get very high (tens to hundreds of gigabytes per second) very quickly. Fortunately several factors mitigate in favor of better performance. The probes themselves share cached texture samples both inter and intra pixel, even with 16 tap anisotropic filtering not all 16 taps are always needed because only distant highly oblique pixel fill tends to be highly anisotropic and such fill tends to cover small regions of the screen and finally magnification texture filters require no anisotropic filtering probes.

See also

★ Bilinear filtering

★ Trilinear filtering

★ Anti-aliasing

External links

★ Side-by-side comparison of trilinear and anisotropic filtering

★ The Naked Truth About Anisotropic Filtering