Recently, non-negative tensor factorization (NTF) as a very powerful tool has attracted the attention of researchers. It is used in unmixing hyperspectral images (HSI) due to its excellent expression ability without any information loss when describing data. However, most existing methods based on NTF fail fully explore unique properties data, for example, low rank, that exists both spectral an...

Recent years have witnessed a trend that uses image representation models, including sparse (SR), low-rank (LRR) and their variants for multi-focus fusion. Despite the thrilling preliminary results, existing methods conduct fusion patch by patch, leading to insufficient consideration of spatial consistency among patches within local region or an object. As result, not only artifacts are easily ...