Real-time multi-scale Retinex to enhance night scene of vehicular camera
Wang-Jun Kyung, Dae-Chul Kim, Yeong‐Ho Ha · 2011
Recently, image processing has been commonly applied to various parts of the vehicle industry. In particular, the use of vehicle cameras gives the driver clear view for occluded regions to the front or rear of the vehicle. However, images from the camera have low visibility at night due to the lack of ambient illumination. To enhance the visibility of images, generic methods using global functions, such as the gamma function, can be used for real time processing, but these methods cannot improve local visibility. In this paper, we propose real time processing of night scene images based on modified multi-scale Retinex(MSR) to enhance the visibility of images from vehicle camera. This method uses integer operations and bit-sifting for real-time computation. In addition, we apply simple blur and mean filters instead of Gaussian convolution to reduce computational cost. Color balance is preserved by obtaining the surround image for the luminance channel only. In the experiments, processing speed approximates to 30 frame per second(FPS) and dark regions in the frames are improved through enhancement of local visibility.