添加了readme说明文件和license文件
carry
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LICENSE
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MIT License
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Copyright (c) 2025 C-a-r-r-y
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
|
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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README.md
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# 计算机视觉与模式识别实验
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本项目包含广州大学计算机视觉与模式识别课程的三个实验，涵盖了图像处理的基础知识和常用技术，使用python+opencv实现。
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## 实验内容
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### 实验1：图像灰度处理与直方图均衡化
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- 图像灰度量化
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- 灰度范围调整
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- 直方图均衡化
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- RGB和HSV色彩空间处理
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### 实验2：形态学图像处理
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- 图像膨胀操作
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- 图像侵蚀操作
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- 图像细化（骨架提取）
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### 实验3：图像噪声处理与滤波
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- 椒盐噪声、高斯噪声、指数噪声的添加
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- 均值滤波、中值滤波、高斯滤波的实现和比较
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- 手动实现中值滤波算法
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## 文件结构
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```
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.
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├── 1-5.ipynb # 实验1代码
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├── 2-5.ipynb # 实验2代码
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├── 3-3.ipynb # 实验3代码
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├── 2-5-4/ # 实验2测试图像
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│ ├── img1.png
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│ ├── img2.png
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│ ├── img3.png
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│ ├── img4.png
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│ ├── img5.png
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│ └── img6.png
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├── circbw.tif # 测试图像
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├── DJI_0049.JPG # 测试图像
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├── Lena.bmp # 测试图像
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├── pout.tif # 测试图像
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├── rice.png # 测试图像
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├── text.png # 测试图像
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└── tire.tif # 测试图像
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```
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## 运行环境
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- Python 3.7+
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- 主要依赖库：
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- NumPy
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- Matplotlib
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- OpenCV
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- scikit-image
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- SciPy
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## 使用说明
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1. 安装依赖库：
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```bash
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pip install numpy matplotlib opencv-python scikit-image scipy
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```
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2. 运行实验代码：
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- 使用Jupyter Notebook打开对应的.ipynb文件
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- 按顺序执行代码单元格
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- 观察图像处理结果和可视化效果
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## 参考
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- 实验内容基于广州大学计算机视觉与模式识别课程
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- 代码实现参考OpenCV和scikit-image官方文档
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