A new remote sensing technique based on video image processing has been developed for the estimation of nearshore bathymetry. The shoreward propagation of waves is measured using pixel intensity time series collected at a cross-shore array of locations using remotely operated video cameras. The incident band is identified, and the cross-spectral matrix is calculated for this band. The cross-shore component of wavenumber is found as the gradient in phase of the first complex empirical orthogonal function of this matrix. Water depth is then inferred from linear wave theory's dispersion relationship. Full bathymetry maps may be measured by collecting data in a large array composed of both cross-shore and longshore lines. Data are collected hourly throughout the day, and a stable, daily estimate of bathymetry is calculated from the median of the hourly estimates. The technique was tested using 30 days of hourly data collected at the SandyDuck experiment in Duck, North Carolina, in October 1997. Errors calculated as the difference between estimated depth and ground truth data show a mean bias of −35 cm (rms error = 91 cm). Expressed as a fraction of the true water depth, the mean percent error was 13% (rms error = 34%). Excluding the region of known wave nonlinearities over the bar crest, the accuracy of the technique improved, and the mean (rms) error was −20 cm (75 cm). Additionally, under low-amplitude swells (wave height H ≤ 1 m), the performance of the technique across the entire profile improved to 6% (29%) of the true water depth with a mean (rms) error of −12 cm (71 cm).