  In recent years, visual sensors have been quickly improving, notably
targeting richer acquisitions of the light present in a visual scene. In this
context, the so-called lenslet light field (LLF) cameras are able to go beyond
the conventional 2D visual acquisition models, by enriching the visual
representation with directional light measures for each pixel position. LLF
imaging is associated to large amounts of data, thus critically demanding
efficient coding solutions in order applications involving transmission and
storage may be deployed. For this reason, considerable research efforts have
been invested in recent years in developing increasingly efficient LLF imaging
coding (LLFIC) solutions. In this context, the main objective of this paper is
to review and evaluate some of the most relevant LLFIC solutions in the
literature, guided by a novel classification taxonomy, which allows better
organizing this field. In this way, more solid conclusions can be drawn about
the current LLFIC status quo, thus allowing to better drive future research and
standardization developments in this technical area.
