# Spectral Visualization Sharpening

arXiv: https://arxiv.org/abs/1907.10208 · HTML: https://mlsanity.com/paper/1907.10208/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Jul 2019.

## Built on by (most cited first, 1 of 1)

- [Self-Supervised Continuous Colormap Recovery from a 2D Scalar Field Visualization without a Legend](https://mlsanity.com/paper/2507.20632/) (2025)

## Abstract (arXiv)

In this paper, we propose a perceptually-guided visualization sharpening technique. We analyze the spectral behavior of an established comprehensive perceptual model to arrive at our approximated model based on an adapted weighting of the bandpass images from a Gaussian pyramid. The main benefit of this approximated model is its controllability and predictability for sharpening color-mapped visualizations. Our method can be integrated into any visualization tool as it adopts generic image-based post-processing, and it is intuitive and easy to use as viewing distance is the only parameter. Using highly diverse datasets, we show the usefulness of our method across a wide range of typical visualizations.