# GPR_3D_attribute

**Repository Path**: sduem/gpr3dattribute

## Basic Information

- **Project Name**: GPR_3D_attribute
- **Description**: Implement ground penetrating radar data processing, offset imaging, attribute analysis, and 3D modeling. This program is used to analyze the restoration status of the Buddha statue of Sumeru.
- **Primary Language**: Python
- **License**: GPL-3.0
- **Default Branch**: master
- **Homepage**: https://git.em3d.cn/openSource/gpr3dattribute
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-06-17
- **Last Updated**: 2025-09-18

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# GPR 3D attribute Imaging Toolkit

This project provides a Python-based workflow for processing ground-penetrating radar (GPR) data from SEG-Y files, performing FK migration, and exporting the results as 3D point cloud data. It includes steps for data correction, background subtraction, tapering, migration, Hilbert envelope computation, and visualization.

# Cite this work
Junkai Ge, Huaifeng Sun, Xiaodong Li, Xushan Lu, Xuening Wang, Li Li, Kejia Hu, Decoding the stone Buddha: Three-dimensional ground penetrating radar attribute insights into cracks and restoration history of Sumeru throne, Journal of Cultural Heritage, Volume 76, November–December 2025, Pages 39-51

See the published paper at
https://www.sciencedirect.com/science/article/pii/S1296207425001980 

## 🌍 Key Features

- Read and process SEG-Y GPR data using `segyio`
- Remove static and background clutter using sliding window averaging
- Apply custom tapering and FK migration
- Generate and visualize migrated sections and Hilbert envelopes
- Export processed results to `.dat` point cloud format for 3D visualization

## 🧩 Dependencies

Make sure you have the following Python packages installed:

```bash
pip install numpy matplotlib scipy segyio math pdb traceback tqdm