Gangadharan, J., Mani, S., and Kutty, K., "Low Light Image Enhancement Using Color Transfer," SAE Technical Paper 2015-01-0312, 2015, doi:10.4271/2015-01-0312.
Advanced Driver Assistance System (ADAS) in combination with other active safety features like air bags etc. is gaining popularity. Vision based ADAS systems perform well under ideal lighting, illumination and environmental conditions. However, with change in illumination and other lighting related factors, the effectiveness of vision based ADAS systems tend to deteriorate. Under conditions of low light, it is therefore important to develop techniques that would offset the effects of low illumination and generate an image that appears as if it were taken under ideal lighting conditions. To accomplish this, we have developed a method, that uses local color statistics from the host image with low illumination, and enhance the same using an adaptive color transfer mechanism. By taking cues from the properties of ideal images that are saved in a database, the proposed method tends to recreate the input scene (with low illumination), into a near ideal scene, based on the database images. Visual and quantitative evaluation of our method confirms that it performs well under very low light conditions as well, where standard algorithms tend to fail.