Recent Intelligent Transportation System (ITS) focuses on both traffic management and Homeland Security. It involves advance detection systems of all kind but proper analysis of the image data is required for controlling and further processing. It becomes even more difficult when it comes to low light images due to limitation in the image sensor and heavy amount of noise. An ITS supports all levels like (Transport policy level, Traffic control tactical level, Traffic control measure level, Traffic control operation). For this it uses several split systems like Real time passenger information (RTPI), Automatic Number Plate Recognition (ANPR), Variable message signs (VMS), Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) system. While analyzing critical scenarios, mostly for the development of the application for Vehicle to Infrastructure (V2I) System several cases are taken into consideration. From these cases some are very difficult to analyze due to the visibility of the background as the detail structure is taken into consideration. Here Direct processing of low light images or video frames like day images leads to loss of required data, so an efficient enhancement method is required which gives allowable result for further transformation and analysis with minimal processing. So an Adaptive Enhancement Method is presented here which applies different enhancement methods for day light and low light images separately. For this purpose a combination of image fusion, edge detection filtering and Contourlet transformation is used for low light images; tone level adjustment and low level feature extraction for enhancement of day light images.