WSHT Algorithm for Improved SHP Selection in DS-InSAR: Robust Performance Across Sample Sizes

The selection of statistically homogeneous pixels (SHPs) is essential for precise deformation monitoring in distributed scatterer synthetic aperture radar interferometry (DS-InSAR). Current SHP selection methods face challenges in test efficacy under small-sample and low-contrast conditions, resulting in imbalanced Type I and Type II errors and poor detection of weak heterogeneity. To address these issues, the wide-scope homogeneous testing (WSHT) algorithm is introduced, which enhances the hypothesis test of confidence interval (HTCI) by calculating the extremes of the confidence interval length and integrating Baumgartner-Weiss–Schindler (BWS) to minimize this length and improve the accuracy of the reference pixel mean. Simulations demonstrate that WSHT outperforms BWS and HTCI, achieving accuracy improvements of 71.00% and 34.71%, respectively. Analysis of Sentinel-1 images from Shenzhen City further highlights WSHT’s performance, achieving the highest SNR of 0.2755, a balanced speckle suppression index (SSI) of 5.5486, and the lowest mean squared error (MSE) of 0.2089, outperforming BWS and HTCI in noise suppression, resolution preservation, and robustness to sample size variations.