docs: Add Case Study 02 to Documentation and Update Parser Usage

README.md

@@ -823,6 +823,7 @@ The visualization shows:
 |----------|-------------|-------------|
 | **01_doctra_quick_start** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1Z9UH9r1ZxGHm2cAFVKy7W9cKjcgBDOlG?usp=sharing) | Comprehensive tutorial covering layout detection, content extraction, and multi-format outputs with visual examples |
 | **case_study_01_financial_report_analysis** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AdemBoukhris457/Doctra/blob/main/notebooks/case_study_01_financial_report_analysis.ipynb) | Financial report analysis: Extract tables and charts from PDF reports, convert visual elements to structured data using VLM, and analyze financial data with pandas |
+| **case_study_02_scanned_document_restoration** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AdemBoukhris457/Doctra/blob/main/notebooks/case_study_02_scanned_document_restoration.ipynb) | Scanned document restoration: Apply DocRes engine for image restoration (appearance, dewarping, deshadowing, deblurring, binarization, end2end), restore PDFs, and compare parsing results before and after restoration |
 
 ## 📖 Usage Examples
 

docs/en/index.md

@@ -108,6 +108,7 @@ parser.parse("document.pdf")
 |----------|-------------|-------------|
 | **01_doctra_quick_start** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1Z9UH9r1ZxGHm2cAFVKy7W9cKjcgBDOlG?usp=sharing) | Comprehensive tutorial covering layout detection, content extraction, and multi-format outputs with visual examples |
 | **case_study_01_financial_report_analysis** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AdemBoukhris457/Doctra/blob/main/notebooks/case_study_01_financial_report_analysis.ipynb) | Financial report analysis: Extract tables and charts from PDF reports, convert visual elements to structured data using VLM, and analyze financial data with pandas |
+| **case_study_02_scanned_document_restoration** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AdemBoukhris457/Doctra/blob/main/notebooks/case_study_02_scanned_document_restoration.ipynb) | Scanned document restoration: Apply DocRes engine for image restoration (appearance, dewarping, deshadowing, deblurring, binarization, end2end), restore PDFs, and compare parsing results before and after restoration |
 
 ## What's Next?
 

docs/zh/index.md

@@ -108,6 +108,7 @@ parser.parse("document.pdf")
 |--------|-----------|------|
 | **01_doctra_quick_start** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1Z9UH9r1ZxGHm2cAFVKy7W9cKjcgBDOlG?usp=sharing) | 涵盖布局检测、内容提取和多格式输出的综合教程，带视觉示例 |
 | **case_study_01_financial_report_analysis** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AdemBoukhris457/Doctra/blob/main/notebooks/case_study_01_financial_report_analysis.ipynb) | 财务报告分析：从 PDF 报告中提取表格和图表，使用 VLM 将视觉元素转换为结构化数据，并使用 pandas 分析财务数据 |
+| **case_study_02_scanned_document_restoration** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AdemBoukhris457/Doctra/blob/main/notebooks/case_study_02_scanned_document_restoration.ipynb) | 扫描文档恢复：应用 DocRes 引擎进行图像恢复（外观、去扭曲、去阴影、去模糊、二值化、端到端），恢复 PDF，并比较恢复前后的解析结果 |
 
 ## 下一步？