Phase unwrapping and denoising for time-of-flight imaging using generalized approximate message passing

We present a new method for simultaneously denoising and unwrapping phase in multi-frequency homodyne time-of-flight ranging for the formation of accurate depth maps despite low SNR of raw measurements. This is achieved with a new generalized approximate message passing (GAMP) algorithm for minimum mean-squared error estimation of the phase. A detailed, physically-accurate acquisition model is central in achieving high accuracy, and the use of the GAMP methodology allows low computational complexity despite dense dependencies and the nonlinearity and non-Gaussianity of the acquisition model. Numerical simulations demonstrate that our integrated approach performs better than separate unwrapping followed by denoising. This performance translates to lowering the optical power consumption of time-of-flight cameras for a fixed acquisition quality.