Depth-resolved wavenumber-scanning interferometry (DRWSI) is used to measure the contours or displacement fields inside a structure. One of the most promising phase retrieving algorithms of DRWSI is the eigenvalue decomposition and least-squares algorithm, because it can blindly evaluate the number of interferometric sources with a fine depth resolution. However, it is not robust to noise, in particular, salt noise or impulse noise. In order to significantly improve the immunity of DRWSI to noise, an updated eigenvalue decomposition algorithm is developed in this manuscript by employing the Spearman’s rank (SR) correlation function as a kernel function. Extreme experimental conditions under an environment with salt noise are designed to verify the performance of the new algorithm in DRWSI, called eigenvalue decomposition using SR correlation and Fourier transform. The results show that it is very effective for the phase reconstruction of DRWSI.