This is the code repository for Jitter-Aware Restoration with Equivalent Jitter Model for Remote Sensing Push-Broom Image.

Simple Run Guide: Step-by-Step Instructions (Detailed guide will be updated later)

1. Set up the Anaconda + Python environment on Linux
   Follow the steps below to configure the necessary environment:

   • Install Anaconda for managing Python environments.
   • Create a new environment:

     conda create --name <env_name> python=3.8
     conda activate <env_name>

2. Upload the code files and download the dataset
   Upload the code files to your server. Then, execute the following command to download and extract the dataset:

   sh down.sh

   Note: Ensure the server is connected to the internet, or manually download and upload the dataset if needed.

3. Install necessary Python libraries
   Install the required libraries using pip:

   pip install -r requirements.txt

4. Generate simulation data

   • To generate TDI simulation data, run the following:

     python data_generate_TDIv2.py

   • To generate LA simulation data, run this:

     python data_generate_LinearArray.py

5. Set paths for training and validation datasets in Options
   Update the Options file to point to the paths of your training and validation datasets.

6. Train the model
   Finally, start the training process by running the following command:

   bash run.sh

Note: This is a simple run guide. A more detailed step-by-step instruction will be provided in future updates.