We present an overview of recent progress in techniques of color image enhancement for night vision in surveillance applications. Inspired by previously developed color constancy schemes, we firstly test simple algorithms in order to enhance dark images. These methods have been successfully deployed in different research areas, however, this enhancing approach occasionally does not produce realistic colors. We continue our discussion, now applying color mapping from daylight images, transferring first order statistics from a target image to the dark one. Particularly, we have explored the use of color transfer algorithms in the RLAB color space, procedure that yields outstanding results, with realistic and vivid colors. Finally, another method commented here, consists of applying the statistical mapping approach in a color look-up table framework, where both color constancy and computational simplicity are achieved. Some experimental results are shown and discussed in order to glimpse the importance of these approaches in surveillance tasks.