# Gaussian kernel smoothing

arXiv: https://arxiv.org/abs/2007.09539 · HTML: https://mlsanity.com/paper/2007.09539/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Jul 2020.

## Built on by (most cited first, 6 of 6)

- [MeGA: Hybrid Mesh-Gaussian Head Avatar for High-Fidelity Rendering and Head Editing](https://mlsanity.com/paper/2404.19026/) (2024)
- [FlowHOI: Flow-based Semantics-Grounded Generation of Hand-Object Interactions for Dexterous Robot Manipulation](https://mlsanity.com/paper/2602.13444/) (2026)
- [Pre-training Epidemic Time Series Forecasters with Compartmental Prototypes](https://mlsanity.com/paper/2502.03393/) (2025)
- [Fully Automated Binary Pattern Extraction For Finger Vein Identification using Double Optimization Stages-Based Unsupervised Learning Approach](https://mlsanity.com/paper/2205.03840/) (2022)
- [Keypoints as Dynamic Centroids for Unified Human Pose and Segmentation](https://mlsanity.com/paper/2505.12130/) (2025)
- [K-Stain: Keypoint-Driven Correspondence for H&E-to-IHC Virtual Staining](https://mlsanity.com/paper/2511.06709/) (2025)

## Abstract (arXiv)

Image acquisition and segmentation are likely to introduce noise. Further image processing such as image registration and parameterization can introduce additional noise. It is thus imperative to reduce noise measurements and boost signal. In order to increase the signal-to-noise ratio (SNR) and smoothness of data required for the subsequent random field theory based statistical inference, some type of smoothing is necessary. Among many image smoothing methods, Gaussian kernel smoothing has emerged as a de facto smoothing technique among brain imaging researchers due to its simplicity in numerical implementation. Gaussian kernel smoothing also increases statistical sensitivity and statistical power as well as Gausianness. Gaussian kernel smoothing can be viewed as weighted averaging of voxel values. Then from the central limit theorem, the weighted average should be more Gaussian.