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Multihypothesis with phase diversity is introduced into motion-compensated temporal filtering by deploying the latter in the domain of a spatially redundant wavelet transform. The centerpiece of this redundant-wavelet approach to multihypothesis temporal filtering is a multiple-phase inverse transform that involves an implicit projection significantly reducing noise not captured by the motion model of the temporal filtering. The primary contribution of the work is a derivation that establishes analytically the advantage of the redundant-wavelet approach as compared to equivalent temporal filtering taking place in the spatial domain. For practical implementation, a regular triangle mesh is used to track motion between frames, and an affine transform between mesh triangles implements motion compensation within a lifting-based temporal transform. Experimental results reveal that the incorporation of phase-diversity multihypothesis into motion-compensated temporal filtering improves rate-distortion performance, and state-of-the-art scalable performance is observed.