A polygon-based interpolation operator for super-resolution imaging
This work addresses super-resolution imaging for applications requiring enhanced image reconstruction, but it appears incremental as it builds on existing interpolation methods.
The paper tackled the super-resolution reconstruction problem by introducing a polygon-based interpolation operator, which outperformed bilinear interpolation and eliminated the need for parameter estimation unlike Gaussian modeling.
We outline the super-resolution reconstruction problem posed as a maximization of probability. We then introduce an interpolation method based on polygonal pixel overlap, express it as a linear operator, and use it to improve reconstruction. Polygon interpolation outperforms the simpler bilinear interpolation operator and, unlike Gaussian modeling of pixels, requires no parameter estimation. A free software implementation that reproduces the results shown is provided.