To　improve　the　observability　of　low-light　images,　a　low-light　image　enhancement　algorithm　based　on　nonsubsampled　shearlet　transform　(NSST)　is　presented　(LIEST).　The　proposed　algorithm　can　synchronously　achieve　contrast　improvement,　noise　suppression,　and　the　enhancement　of　specific　directional　details.　An　enhancement　framework　of　low-light　noisy　images　is　first　derived,　and　then,　according　to　the　framework,　a　low-light　noisy　image　is　decomposed　into　low-pass　subband　coefficients　and　bandpass　direction　subband　coefficients　by　NSST.　Then,　in　the　NSST　domain,　an　illumination　map　is　estimated　based　on　a　bright　channel　of　the　low-pass　subband　coefficients,　and　noise　is　simultaneously　suppressed　by　shrinking　the　bandpass　direction　subband　coefficients.　Finally,　based　on　the　estimated　illumination　map,　the　low-pass　subband　coefficients,　and　the　shrunken　bandpass　direction　subband　coefficients,　inverse　NSST　is　implemented　to　achieve　low-light　image　enhancement.　Experiments　demonstrate　that　the　LIEST　exhibits　superior　performance　in　improving　contrast,　suppressing　noise,　and　highlighting　specific　details　as　compared　to　seven　similar　algorithms.　©　2013　IEEE.