Filtering an ALOS-PALSAR Dataset with Hanning-Window

All results and some explanations can be found in the notebook hann_window_alospalsar.ipynb.

Summary

I wrote a notebook to visualize an ALOS-PALSAR L1.1 dataset, and to demonstrate the effect of applying a filter in the frequency domain. In short, the filter (i.e., the Hanning-window) decreases the noise level and---more importantly---reduces the level of the sidelobes caused by the PSF in range. This effect is shown in the figure below.

Fig. 1: Demonstration of the effect of applying the Hanning window in the range frequency domain. The figure shows the area around Matsuyama airport without (left) and with filtering (right).

The full scene before and after filtering with the Hanning-window is shown in the following figures.

Fig. 2: Full PALSAR scene before filtering.

Fig. 3: Full PALSAR scene after filtering.

The Hanning-window that is used for filtering in the frequency domain is shown in Fig. 4.

Fig. 4: Hanning-window used for filtering in the range frequency domain.

How to Run the Code

1. Use Python3.7+ (I created this code in Python3.8).

2. Create virtual environment with a tool of your choice (I used mkvirtualenv from the virtualenvwrapper).

3. Install dependencies

   • If you use poetry, just run

   poetry install

   in the main directory of the repository. This will install all the required dependencies.

   • If you prefer pip, run

    pip3 install -r requirements.txt 

4. Start a Jupyter Notebook server:

   jupyter notebook

5. Inside Jupyter, navigate into the directory notebooks and open the notebook hann_window_alospalsar.ipynb. Execute the code cells and follow the instructions in the markdown cells.

NOTE

Inside the notebook containing the main code, a lot of arrays are created for the purpose of visualization and interaction. This is not ideal, of course, as the because each takes up a lot of memory. I didn't mind that, because I have 128GB of RAM at my disposal. Should there be any problems running the notebook due to memory issues, please let me know, and I can make adjustments for the code to be a bit resource friendlier.