GamingGPUs

PC Graphics Settings Explained: MLAA vs MSAA vs FXAA vs TAA vs SMAA

TAA, SMAA, FXAA, MSAA, MLAA, or SSAA, which one should you choose? Four options and this is just anti-aliasing we’re talking about here. Modern games include a slew of graphics settings to choose from, in order to get the best performance for your hardware. Other than Anti-Aliasing (AA), you’ve got Ambient Occlusion, Screen Space Reflections, Shadows, Texture Filtering, Post-Processing, and much more. What do all these graphics settings do, and more importantly how do they impact the visual fidelity in your favorite games? Let’s find out!

Anti-Aliasing: MSAA vs FXAA vs SMAA vs TAA

Let’s start off with anti-aliasing. It’s one of the primary graphics settings you’ll find in games. You’ve got the traditional MSAA, SSAA, FXAA, and the newer shader-based SMAA and temporal techniques (TAA) that have become the norm. So, what does anti-aliasing do? In short, it gives the image a cleaner look by removing the rough or jagged edges around objects.

No AA

FXAA

Above’s an example of how FXAA (fast approximate anti-aliasing) improves the image quality by reducing the jaggies. Enlarge the images and see how the second one is notably smoother. Here’s a comparison of how AA impacts your game. Below you can see SMAA in action:

No AA
SMAA

The differences are subtle but exist across the entire image. Check the electric pole and the wiring. They lose the teeth on the edges when SMAA is turned on. The buntings and the vegetation also get the same treatment. However, unlike FXAA, SMAA isn’t too strong. It gets rid of the aliasing, without blurring the texture detail.

There are two main types of anti-aliasing techniques:

Traditional sampling-based methods: These include MSAA (Multi-sampling AA) and SSAA (Super Sampling AA) which were popular last-gen and for good reason. They produce the best image quality (broadly speaking) but the performance hit is severe. They work by rendering the image at a higher resolution and then scaling it down to fit the native resolution. This essentially makes the entire image sharper and more detailed, scaling down the rough edges in the process but not removing them entirely. Here’s an example:

Downscaling in NVIDIA DSR

Super Sampling renders the entire image at a higher resolution and then scales it down to fit the target resolution. The exact rendering resolution depends on the developer. The image can be rendered at a higher resolution along both the x and y-axis or one of them (and then downsampled). Downsampling can be done in a variety of ways. The most popular method involves finding the average pixel color of a bunch of adjacent pixels (or the triangles/quads within them) and then using it to calculate the resultant downscaled pixel.

Deferred Rendering

MSAA or multi-sampling uses edge-detection algorithms to detect aliasing (based on contrast differences) and then renders only those pixels at a higher (sampling rate or) resolution. Once again, the amount of additional sampling varies from 2x to 8x. In most cases, SSAA and MSAA miss transparent textures as most edge detection filters fail to recognize them. Furthermore, they tend to reduce the intensity of aliasing, rather than completely eliminate it. Another additional drawback of MSAA is that it can’t be used with deferred lighting techniques which are quite popular in modern games. Deferred lighting or rendering basically delays the calculation of the lighting from the vertex shader to fragment shader (which is basically a pre-calculation of the pixel shader). This saves a lot of performance as applying lighting on a vertex basis would mean calculating it for several millions of polygons. In the case of fragments, you’re usually calculating it on a fragment basis which generally corresponds to the target output resolution.

No AA
2x MSAA

Shader-based AA techniques: are more efficient and don’t bring down the performance by much. They work by applying a blur filter to the scene, making the image smoother but at the same time reducing the sharpness:

FXAA is a good example of how shader-based AA gets rid of aliasing but reduces the level of detail as well. This is because FXAA uses luma or contrast-based edge detection (AA is applied wherever the luma difference is higher than a certain threshold). This isn’t very accurate and tends to blur objects with complex multi-colored patterns. FXAA can also treat sub-pixel AA. This is done by taking a square (3×3) grid and comparing the luma of outer pixels to that of the central pixel. The smaller the contrast difference between the two, the less aliased it will be.

Newer methods such as SMAA greatly reduce the blur intensity while also eating up most of the jaggies. However, it suffers from the same drawback as MSAA: It doesn’t work with transparent textures.

No AA vs FXAA
MLAA

Morphological Anti-aliasing (MLAA) was one of the first shader-based AA techniques to gain widespread adoption. It is implemented in the last stage of the rendering pipeline (post-processing) and works by searching for discontinuities (see the perpendicular green line at a) and classifies them according to a series of pre-defined pattern shapes. They are then virtually re-vectorized (blue line), allowing the calculation of the coverage areas for the involved pixels. These areas are then used to blend with a neighbor, therefore smoothening them out. The shaded pixels (here a) get a color depending on the surrounding pixels. The edge detection is carried out using depth or luma information, pattern detection, and calculation of coverage areas (given by C). Pattern detection searches the two ends of an edge and analyzing the crossing edges.

Coverage areas are shown in green

One of the primary drawbacks of MLAA is that it doesn’t work well with geometry that contains a lot of thin lines and objects. It was designed to anti-alias silhouettes of objects, and as such with sharp geometric features it results in blurry results:

SMAA was introduced to rectify the shortcomings of both FXAA (too much blurring) and MLAA (limited coverage), and it works well in most scenarios. It works by leveraging edge-detection based on color-specific luma, and searching the edges at the top and left of every pixel while retrieving the other two from neighboring pixels.

SMAA uses multiple (1-pixel long for sharp geometry and multiple pixels long for diagonal patterns) crossing lines to enhance the edge detection and not only reduce blurring, but also improve coverage. With thin lines and objects prone to blurring with FXAA/MLAA, a rounding factor is used which scales the coverage areas obtained by the pixel-long crossing edges.

SMAA is often paired with temporal anti-aliasing (SMAA T1x/T2x) which uses temporal data from neighboring frames to improve the stability and quality of anti-aliasing. Furthermore, unlike MLAA, SMAA uses multiple samples per pixel which allows for improved image quality. The usual value is two but in some cases, four are also used. The following modes are usually considered viable for SMAA:

  • SMAA 1x: includes accurate distance searches, local contrast adaptation, sharp geometric features, and diagonal pattern detection.
  • SMAA S2x: includes all SMAA 1x features plus spatial multi-sampling.
  • SMAA T2x: includes all SMAA 1x features plus temporal super-sampling.
  • SMAA 4x: includes all SMAA 1x features plus spatial and temporal multi/super-sampling

The latest and most popular form of AA is temporal anti-aliasing. TAA focuses on removing temporal aliasing or shimmering. It’s most evident in motion. Temporal aliasing is caused when the frame rate is too low compared to the transition speed of the objects in the scene. This makes the boundaries of the objects appear in motion. TAA works by comparing neighboring frames (temporally) and blending them to create a cleaner image in motion.

The present frame is rendered along with the geometry and shading, after which it is reprojected on the previous image using the jitter offsets and motion vectors. After that a rectify filter is used to compare the frame and check for any ghosting, after which the post-processing effects are applied, thereby completing the frame. Similarly, this frame is used for reconstructing (by reprojection) the next consecutive frame, and the process continues.

TAA (right)

As TAA is essentially an approximation of sorts: It uses two images to extrapolate the final image, it also causes a good deal of blurring, losing some texture detail in the process. This is evident in the above image. The image is rendered across different frames at a particular resolution, and with each additional image, a jitter offset (camera shift of a few pixels) is applied. This produces multiple images from a single frame which are then used for supersampling and/or upscaling.

Temporal upscaling uses a similar method to upscale lower-resolution images. The core difference is that, unlike TAA, alternating pixels are rendered in consecutive frames, and filling the gaps using interpolation and samples from the neighboring pixels.

Here’s a comparison of FXAA vs TAA used on the same image:

TAA
FXAA

The main advantages of TAA over FXAA are more pronounced in motion. The “teeth” at the boundaries of the objects appear to be moving when you are in motion in-game. TAA works to smoothen these artifacts while FXAA simply applies a “Vaseline filer” which although effective, produces curvy lines that jump around when there’s a transition in the scene.

Ambient Occlusion

Continued on the next page…

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Areej

Computer Engineering dropout (3 years), writer, journalist, and amateur poet. I started my first technology blog, Techquila while in college to address my hardware passion. Although largely successful, it was a classic example of too many people trying out multiple different things but getting nothing done. Left in late 2019 and been working on Hardware Times ever since.

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