In this paper, we present a new wavelet-based estimator for 2-D multichannel signals. Estimation of a 2-D multichannel signal relies on the ability to decorrelate the signal in both space and channel. The new estimator we present uses a 2-D discrete wavelet transform to approximately decorrelate the signal in space, allowing for efficient estimation of both stationary and nonstationary signals. When channel correlation is unknown, but depends only on channel separation, the DFT may be utilized to decorrelate the channel efficiently. In contrast to the optimal estimation scheme, our new estimator does not require second-order signal statistics, making it well suited to many applications. In addition to providing vastly improved visual quality, the new estimator typically yields signal-to-noise ratio gains of over 12 dB.