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Several algorithms have been proposed for multichannel blind deconvolution of images. Many of these algorithms are critically dependent on accurate estimates of the sizes of the unknown filters-wrong estimates can result in catastrophic failure. In this paper we present a residual-based technique for order estimation that is based on the generalized likelihood ratio test (GLRT). The performance of the algorithm is shown to be far superior to subspace rank-based methods typically used for the purpose. We conjecture that the algorithm fails only when the data is corrupted to an extent that makes any kind of reconstruction infeasible.