Preprint Open access
Robust Tensor Completion via Reflective Convolution Nuclear Norm Minimization
Robust tensor completion recovers multidimensional data from partial observations corrupted by sparse gross errors. Existing convolutional low-rank models typically construct translated copies using circular continuation, which introduces artificial wrap-around neighborhoods for finite nonperiodic data. We propose refl …