MATLAB Code for InSAR Data Processing - Complete Workflow Implementation

This document presents the complete workflow for InSAR data processing using MATLAB code:

First, we calculate the phase differences between each pair of SAR images. This requires implementing image processing algorithms such as phase correlation methods. In MATLAB, this can be achieved using functions like normxcorr2 for normalized cross-correlation or custom implementations using fast Fourier transforms (FFT) to compute phase correlation coefficients between image pairs.

Next, we utilize these phase differences to generate topographic elevation maps. This involves employing interpolation algorithms such as bicubic interpolation. MATLAB's griddata function with 'cubic' option or the interp2 function can be used for implementing bicubic interpolation, which provides smooth elevation surfaces while preserving important terrain features.

Subsequently, we convert the topographic elevation maps into surface deformation maps. This step requires deformation analysis algorithms like registration methods. MATLAB's imregister function with optimization algorithms (such as gradient descent) can be employed for precise image registration, or alternatively, implement phase unwrapping algorithms using Goldstein's method or minimum cost flow approaches to resolve phase ambiguities.

Finally, we visualize the surface deformation maps to better understand ground motion patterns. MATLAB's mapping toolbox provides functions like geoshow and contourf for creating professional deformation visualizations, while custom color maps can be designed using colormap editor to highlight deformation gradients effectively.

We hope this information proves valuable for your InSAR processing projects. For additional technical assistance or code customization, please feel free to contact our support team.