In this paper, we study the various approaches and methodologies used for face hallucination. Face hallucination was first presented as high-resolution image from a low-resolution image. The numerous applications of this method include in the field of image enhancement, face recognition surveillance and security. It is useful in surveillance and security system to enhance the a low-resolution face which possesses facial details matching that of a potential high-resolution image, helping in further analysis. In this paper we have analysed various approaches for enhancing low-resolution images namely, Face Hallucination (FH) with Sparse Representation, FH using Eigentransformation, FH via Locality Constraint Representation, learning-based FH in DCT (Discrete Cosine Transform) domain.