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The interpolation data in the lookup tables are constrained by the requirement that continuity of line segments must be preserved, while optimizing for smoothness. Generating these lookup tables is relatively slow, and is the major source of complexity in the algorithm: the render stage is very simple and fast, and designed to be capable of being performed in real time.
The interpolation data in the lookup tables are constrained by the requirement that continuity of line segments must be preserved, while optimizing for smoothness. Generating these lookup tables is relatively slow, and is the major source of complexity in the algorithm: the render stage is very simple and fast, and designed to be capable of being performed in real time.

==See also==

* [[Image scaling]]


==External links==
==External links==

Revision as of 10:14, 25 July 2015


In image processing, hqx ("hq" stands for "high quality" and "x" stands for magnification) is one of the pixel art scaling algorithms developed by Maxim Stepin, used in emulators such as Nestopia, FCEUX, higan, Snes9x, ZSNES and many more. There are three hqx filters: hq2x, hq3x, and hq4x, which magnify by factor of 2, 3, and 4 respectively. For other magnification factors, this filter is used with nearest-neighbor scaling.

Image enlarged 3× with the nearest-neighbor interpolation
Image enlarged by 3× with hq3x algorithm

Algorithm

First, the color of each of the 8 pixels around the source pixel is compared to the color of the source pixel. Shapes are detected by checking for pixels of similar color according to a threshold. This gives total of 28 = 256 combinations of similar or dissimilar neighbors. To expand the single pixel into a 2×2, 3×3, or 4×4 block of pixels, the arrangement of neighbors is looked up in a predefined table which contains the necessary interpolation patterns.

The interpolation data in the lookup tables are constrained by the requirement that continuity of line segments must be preserved, while optimizing for smoothness. Generating these lookup tables is relatively slow, and is the major source of complexity in the algorithm: the render stage is very simple and fast, and designed to be capable of being performed in real time.

See also