A Visibility Improvement System for Low Vision Drivers by Nonlinear Enhancement of Fused Visible and Infrared Video

Abstract

Development of a visibility improvement system for helping drivers with poor vision during night and bad weather conditions is proposed in this paper. Video streams captured by a CCD camera and an infrared camera are registered and fused to obtain image details in extremely low lighting conditions. A novel image enhancement technique employing a nonlinear expansion function is developed for enhancing the fused images. The slope characteristics of the expansion function at an individual pixel location is based on the statistical properties of its neighborhood pixels. The expansion function is also capable of reducing the intensity of the overly bright image regions due to the presence of head lights from vehicles in opposite direction. The enhanced video stream is then subjected to a color restoration process to introduce natural color using the color information gathered from the CCD camera image. The entire image processing and analysis system is being installed in an FPGA environment for performing the processing in real-time. The processed video stream is displayed on a Head-Up Display located directly in front of the driver to assist him/her to drive safely in poor visibility environments. Preliminary results obtained in various experiments conducted with the proposed system are encouraging.