# Gaussian Fourier Pyramid for Local Laplacian Filter

arXiv: https://arxiv.org/abs/2206.04681 · HTML: https://mlsanity.com/paper/2206.04681/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 28 references that are in the map.
- First posted on arXiv 8 Jun 2022.

## Builds on (most cited first, 1 of 1)

- [Fast High-Dimensional Kernel Filtering](https://mlsanity.com/paper/1901.06112/) (2019)

## Abstract (arXiv)

Multi-scale processing is essential in image processing and computer graphics. Halos are a central issue in multi-scale processing. Several edge-preserving decompositions resolve halos, e.g., local Laplacian filtering (LLF), by extending the Laplacian pyramid to have an edge-preserving property. Its processing is costly; thus, an approximated acceleration of fast LLF was proposed to linearly interpolate multiple Laplacian pyramids. This paper further improves the accuracy by Fourier series expansion, named Fourier LLF. Our results showed that Fourier LLF has a higher accuracy for the same number of pyramids. Moreover, Fourier LLF exhibits parameter-adaptive property for content-adaptive filtering. The code is available at: https://norishigefukushima.github.io/GaussianFourierPyramid/.