Quaternion Nonlinear Transform-Induced Nuclear Norm for Low-Rank Tensor Completion

ArXi:2605.01467v1 Announce Type: cross Tensor completion has emerged as a powerful framework for recovering missing data in multidimensional signals by exploiting low-rank tensor structures. Among existing approaches, linear transform-based tensor nuclear norm (TNN) methods have achieved considerable success by enforcing low-rankness on transformed frontal slices. However, the low-rank structure revealed by linear transforms remains inherently limited.