A weighted error metric and optimization method for antialiasing patterns

Displaying a synthetic image on a computer display requires determining the colors of individual pixels. To avoid aliasing, multiple samples of the image can be taken per pixel, after which the color of a pixel may be computed as a weighted sum of the samples. The positions and weights of the samples play a major role in the resulting image quality, especially in real-time applications where usually only a handful of samples can be afforded per pixel. This paper presents a new error metric and an optimization method for antialiasing patterns used in image reconstruction. The metric is based on comparing the pattern against a given reference reconstruction filter in spatial domain, and it takes into account psychovisually measured angle-specific acuities for sharp features.