HLO: Half-kernel Laplacian Operator for surface smoothing

This paper presents a simple yet effective method for feature-preserving surface smoothing: HLO. We show that our method can preserve features better than the popular uniform Laplacian-based denoising and it significantly alleviates the shrinkage artifact. Extensive experimental results demonstrate that HLO is better than or comparable to state-of-the-art techniques both qualitatively and quantitatively and that it is particularly good at handling meshes with high noise.

Problem setting

This paper presents a simple yet effective method for feature-preserving surface smoothing: HLO. We show that our method can preserve features better than the popular uniform Laplacian-based denoising and it significantly alleviates the shrinkage artifact. Extensive experimental results demonstrate that HLO is better than or comparable to state-of-the-art techniques both qualitatively and quantitatively and that it is particularly good at handling meshes with high noise.

In the broader publication record, this work appears in Computer-Aided Design, 121:102807. The visual notes below pair the paper’s original figures with a concise reading of the method, experimental setup, and reported results.

Method and visual evidence

The method operates on discrete geometry and is designed to preserve meaningful shape structure while filtering noise, estimating features, or improving downstream geometric processing.

The extracted figures below show the geometry-processing pipeline, representative shapes, and visual or numerical comparisons.

Method overview. This image is extracted from an embedded PDF image object on page 3, then recomposed for web display.

Representation and setup. This image is extracted from an embedded PDF image object on page 5, then recomposed for web display.

Experimental evidence. This image is extracted from an embedded PDF image object on page 6, then recomposed for web display.

Result comparison. This image is extracted from an embedded PDF image object on page 7, then recomposed for web display.

Additional visual result. This image is extracted from an embedded PDF image object on page 8, then recomposed for web display.

Results and impact

The evaluation reported in Computer-Aided Design, 121:102807 uses the extracted figures above to show the method’s measurement, reconstruction, segmentation, matching, or diagnostic behavior on representative experiments. These visuals are paired with the paper’s quantitative or qualitative analysis to make the workflow easier to inspect from the homepage.

Source handling

I extracted 9 candidate image objects from paper.pdf and generated the compressed WebP figures used on this page.