Moving Light Adaptive Colonoscopy Reconstruction via Illumination-Attenuation-Aware 3D Gaussian Splatting
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866908927292080128 |
|---|---|
| author | Wang, Hao Zhou, Ying Zhao, Haoyu Wang, Rui Hu, Qiang Zhang, Xing Li, Qiang Wang, Zhiwei |
| author_facet | Wang, Hao Zhou, Ying Zhao, Haoyu Wang, Rui Hu, Qiang Zhang, Xing Li, Qiang Wang, Zhiwei |
| contents | 3D Gaussian Splatting (3DGS) enables real-time view synthesis in colonoscopy but assumes static illumination, making it incompatible with the strong photometric variations caused by the moving light source and camera. This mismatch leads existing methods to compensate for illumination attenuation with structure-violating Gaussians, degrading geometric fidelity. Prior work considers only distance-based attenuation and overlooks the physical characteristics of colonscopic lighting. In this paper, we propose ColIAGS, an improved 3DGS framework for colonoscopy. To mimic realistic appearance under varying illumination, we introduce a lighting model with two types of illumination attenuation factors. To satisfy this lighting model's approximation and effectively integrate it into the 3DGS framework, we design Improved Geometry Modeling to strengthen geometry details and Improved Appearance Modeling to implicitly optimize illumination attenuation solutions. Experimental results on standard benchmarks demonstrate that ColIAGS supports both high-quality novel-view synthesis and accurate geometry reconstruction, outperforming state-of-the-art methods in rendering fidelity and Depth MSE. Our code is available at https://github.com/haowang020110/ColIAGS. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_18739 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Moving Light Adaptive Colonoscopy Reconstruction via Illumination-Attenuation-Aware 3D Gaussian Splatting Wang, Hao Zhou, Ying Zhao, Haoyu Wang, Rui Hu, Qiang Zhang, Xing Li, Qiang Wang, Zhiwei Computer Vision and Pattern Recognition 3D Gaussian Splatting (3DGS) enables real-time view synthesis in colonoscopy but assumes static illumination, making it incompatible with the strong photometric variations caused by the moving light source and camera. This mismatch leads existing methods to compensate for illumination attenuation with structure-violating Gaussians, degrading geometric fidelity. Prior work considers only distance-based attenuation and overlooks the physical characteristics of colonscopic lighting. In this paper, we propose ColIAGS, an improved 3DGS framework for colonoscopy. To mimic realistic appearance under varying illumination, we introduce a lighting model with two types of illumination attenuation factors. To satisfy this lighting model's approximation and effectively integrate it into the 3DGS framework, we design Improved Geometry Modeling to strengthen geometry details and Improved Appearance Modeling to implicitly optimize illumination attenuation solutions. Experimental results on standard benchmarks demonstrate that ColIAGS supports both high-quality novel-view synthesis and accurate geometry reconstruction, outperforming state-of-the-art methods in rendering fidelity and Depth MSE. Our code is available at https://github.com/haowang020110/ColIAGS. |
| title | Moving Light Adaptive Colonoscopy Reconstruction via Illumination-Attenuation-Aware 3D Gaussian Splatting |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2510.18739 |