What is Non-Negative Matrix Factorization (NMF)

A recently developed, biologically inspired method for nonlinearly finding purely additive, sparse, linear, and low-dimension representations of non-negative multivariate data to consequently make latent structure, feature or pattern in the data clear. NMF makes all representation components non-negative (only purely additive representations are allowable) and nonlinearly implements dimension reduction. Psychological and physiological evidence for NMF is that perception of the whole is based on perception of its parts, which is compatible with the intuitive notion of combining parts to form a whole, therefore it is considered to grasp the essence of intelligent or biological data representation in some degree.

Image Inpainting as an Evolving Topic in Image Engineering

Yu-Jin Zhang (Department of Electronic Engineering, Tsinghua University, China)