Skip to content

Latest commit

 

History

History
80 lines (59 loc) · 5.08 KB

README.md

File metadata and controls

80 lines (59 loc) · 5.08 KB
Raw

Cheap Upscaling Triangulation

Cheap Upscaling Triangulation (CUT) is a family of single-image upscaling algorithms for retro and modern games designed to be:

  • Versatile: can upscale from and to any image resolution and are applicable to all the 2D and 3D consoles that Lemuroid supports
  • Efficient: keep the number of samples and calculations as low as possible to minimize battery consumption

In order to achieve this, we need to CUT some corners... Literally!

Algorithms

The family is made by three algorithms CUT1, CUT2 and CUT3, that share the same fundamental steps:

  • Triangulation: Inspired by the method in [1], we analyze the luma plane of each 2x2 square to determine whether it has a vertical, horizontal, or diagonal orientation. For diagonal orientations, we split the square into two triangles.
  • Pattern Recognition: We examine neighboring samples and the results from the triangulation to create an interpolation function for each side of the square.
  • Interpolation: Using the triangulation and the side-specific interpolation functions, we interpolate colors within the square or triangles.

The three algorithms have different levels of quality and features:

  • Passes: Number of passes required to render the final image. Except for the last pass, each step outputs a buffer with the same resolution as the input image.
  • Samples: Number of texture samples.
  • Angle Resolution: The minimal angle the algorithm can accurately represent. Using an approach similar to [2], CUT3 can follow these edges more precisely.
  • Soft Edges: CUT2 and CUT3 enhance the definition of edges wider than one pixel, significantly improving the handling of anti-aliased content.
Algorithm Passes Samples Angle Resolution Soft-Edges Handling
CUT1 1 4*O 45 No
CUT2 2 12*I + 5*O 30 Yes
CUT3 3 12*I + 4*D*I + 5*O Configurable Yes
  • I: Input image resolution
  • O: Output image resolution
  • D: Edge search distance in each direction (tied to angle resolution)

Results

Check a simple webapp that applies the filters to some game screenshots:

https://swordfish90.github.io/cheap-upscaling-triangulation/

Configuration

The look of every variant can be customized with a set of parameters:

// Available in CUT1, CUT2 and CUT3
#define USE_DYNAMIC_BLEND 1                 // Dynamically blend color with respect to contrast
#define BLEND_MIN_CONTRAST_EDGE 0.0         // Minimum contrast level at which sharpness starts increasing [0, 1]
#define BLEND_MAX_CONTRAST_EDGE 1.0         // Maximum contrast level at which sharpness stops increasing [0, 1]
#define BLEND_MIN_SHARPNESS 0.0             // Minimum sharpness level [0, 1]
#define BLEND_MAX_SHARPNESS 1.0             // Maximum sharpness level [0, 1]
#define STATIC_BLEND_SHARPNESS 0.5          // Sharpness level used when dynamic blending is disabled [0, 1]
#define EDGE_USE_FAST_LUMA 0                // Use quick luma approximation in edge detection
#define EDGE_MIN_VALUE 0.05                 // Minimum luma difference used in edge detection [0, 1]

// Available in CUT2 and CUT3
#define SOFT_EDGES_SHARPENING 1             // Enable soft-edges sharpening
#define SOFT_EDGES_SHARPENING_AMOUNT 0.75   // Maximum size reduction of soft-edges pixels (antialiased pixels) [0, 1]

// Available in CUT3
#define SEARCH_MIN_CONTRAST 0.5             // Minimum relative contrast for search to include current pattern [0, 1]
#define SEARCH_MAX_DISTANCE 8               // Maximum search distance in each direction (N,E,S,W) to find a continuous edge [1, ∞[

Performances

There aren't yet extensive performance tests, but I tried measuring GPU load on my device, a Galaxy S21 FE with Snapdragon 888 playing Final Fantasy VI Advance.

Filter GPU Utilization Resolution
Bilinear (Lemuroid) ~1.5% 160p
HQx2 (Retroarch) ~2.5% 320p
CUT1 (Lemuroid) ~3.5% 1080p
HQx4 (Retroarch) ~4.5% 640p
CUT2 (Lemuroid) ~5.5% 1080p
CUT3 (Lemuroid) ~6.5% 1080p
xbrz-freescale-multipass (Retroarch) ~15.0% 1080p

References

  • [1] D. Su and P. Willis, "Image interpolation by pixel level data-dependent triangulation", Computer Graphics Forum, pp. 23, 2004.
  • [2] A. Reshetov, "Morphological antialiasing", Proceedings of the Conference on High Performance Graphics 2009, pp. 109-116, 2009.