Anti-Aliasing

DLAA / DLSS

  • Deep learning approaches.

  • Use dedicated HW (tensor cores) for learned reconstruction.

  • Can be used purely for AA (DLAA) or for upscaling+AA (DLSS).

  • Good quality but hardware- and driver-dependent.

  • Neural-network–based temporal method, no upscaling. Produces very high-quality AA, sharper than TAA, with excellent stability and minimal ghosting.

  • Limitation: only available on RTX-class GPUs with Tensor cores.

SMAA (Subpixel Morphological Anti-Aliasing)

  • Screen-space post-process filter.

  • Enhanced morphological approach with pattern detection and optional temporal/supersampling modes.

  • Better quality than FXAA for subpixel details.

  • Image-based edge detection + pattern matching + blending. Optional SMAA T2x  (temporal) and SMAA 4x  (spatial + temporal + supersampling) modes.

  • Pros:

    • Good quality / cost balance; preserves more detail than FXAA.

    • Preserves more detail than FXAA/MLAA.

    • Detects diagonal/subpixel edges better.

    • Simple to integrate (one or two passes).

    • Stable cost, doesn’t require motion vectors.

  • Cons:

    • Still a post-process (no true geometric sampling), optional temporal features add complexity.

    • Still a screen-space morphological filter: cannot fix shader aliasing or subpixel shimmering in motion.

    • Higher cost than FXAA but still lighter than MSAA/TAA.

    • Temporal variants (T2x, 4x) require history management, increasing complexity.

CMAA (Conservative Morphological Anti-Aliasing)

  • Screen-space post-process filter.

  • Lightweight post-process edge filter, designed as a cheaper alternative to SMAA/FXAA.

  • Its design goals are to be a better alternative to FXAA by:

    1. Being minimally invasive so it can be acceptable as a replacement in a wide range of applications, including worst case scenarios such as text, repeating patterns, certain geometries (power lines, mesh fences, foliage), and moving images.

    2. Running efficiently on low-medium range GPU hardware, such as integrated GPUs (or, in our case, mobile GPUs).

  • CMAA has four basic logical steps:

    1. Image analysis for colour discontinuities (afterwards stored in a local compressed 'edge' buffer). The method used is not unique to CMAA.

    2. Extracting locally dominant edges with a small kernel. (Unique variation of existing algorithms.)

    3. Handling of simple shapes.

    4. Handling of symmetrical long edge shapes. (Unique take on the original MLAA shape handling algorithm.)

  • Pros:

    • Very low GPU cost.

    • Preserves sharpness better than FXAA in many cases.

    • Good fit for low-power or bandwidth-limited platforms.

  • Cons:

    • Lower quality than SMAA (weaker on diagonal/subpixel edges).

    • No temporal stability; flickering/shimmering remains in motion.

    • Less widely adopted/documented compared to SMAA.

  • Samsung - Using CMAA to improve visuals .

FXAA (Fast Approximate Anti-Aliasing)

  • Single-pass post-process edge detection + blur across edges. Very cheap.

  • Pros:

    • Minimal cost, easy to integrate.

  • Cons:

    • Blurs fine detail; cannot fix shader aliasing that is not visible as contrast edges.

TAA / TXAA (Temporal Anti-Aliasing)

  • About and implementation details .

  • TXAA is Nvidia’s branded temporal approach that combines MSAA + post filters.

  • Reduced motion blur, but has a lot of overall blur.

  • Jitter camera/sample positions per frame; blend current frame with reprojected history using motion vectors.

  • Pros:

    • Very effective at removing temporal shimmer and approximating supersampling without shading every sample.

  • Cons:

    • Requires motion vectors, depth history, good stationary/visibility rejection; can cause ghosting and blur; tuning is scene- and engine-dependent.

  • Opinions :

    • Playing some modern games can be really fatiguing because TAA makes things look just out-of-focus enough to find myself reflexively squinting at them, which ain't great for eye-health.

MSAA (Multisample Anti-Aliasing)

  • Vulkan#Multisampling Anti-Aliasing (MSAA) .

  • Vulkan Sample .

  • Multiple coverage samples per pixel calculated during rasterization; shading can be either per-sample or per-pixel depending on pipeline settings.

  • Pros:

    • Correct geometric edge AA, stable across frames, no history artifacts.

  • Cons:

    • Multiplies memory bandwidth and (potentially) fragment-shading cost.

    • Poor fit for deferred shading unless you maintain multisampled G-buffers or use expensive workarounds.

  • MSAA in Vulkan .

    • Cool.

  • Advanced video on the subject .

    • I don't like this guy AT ALL, omfg.

MFAA (Multi-Frame Sampled Anti-Aliasing)

  • Driver/GPU alternates sample patterns across frames and accumulates to approximate higher-sample MSAA cheaply. Driver-level, not always available.

  • Can achieve MSAA-like appearance at lower immediate cost, but depends on driver & GPU; not a universal solution for engine-level integration.

  • NVIDIA - MSAA and MFAA .