Images captured at low light suffers from underexposure and noise. These poor-quality images act as hindrance for computer vision algorithms as well as human vision. While this problem can be solved by increasing the exposure time, it also introduces new problems. In applications
like ADAS, where there are fast moving objects in the scene, increasing the exposure time will cause motion blur. In applications, that demand higher frame rate, increasing the exposure time is not an option. Increasing the gain will result in noise as well as saturation of pixels at higher
end. So, a real time scene adaptive algorithm is required for the enhancement of low light images. We propose a real time low light enhancement algorithm with more detail preservation compared to existing global based enhancement algorithms for low cost embedded platforms. The algorithm is
integrated to image signal processing pipeline of TI’s TDA3x and achieved ˜50fps on c66x DSP for HD resolution video captured from Omnivision’s OV10640 Bayer image sensor.