Reflection removal for in-vehicle black box videos

Abstract

The in-vehicle black box camera (dashboard camera) has become a popular device in many countries for security monitoring and event capturing. The readability of video content is the most critical matter, however, the content is often degraded due to the windscreen reflection of objects inside. In this paper, we propose a novel method to remove the reflection on the windscreen from in-vehicle black box videos. The method exploits the spatio-temporal coherence of reflection, which states that a vehicle is moving forward while the reflection of the internal objects remains static. The average image prior is proposed by imposing a heavy-tail distribution with a higher peak to remove the reflection. The two-layered scene composed of reflection and background layers is the basis of the separation model. A non-convex cost function is developed based on this property and optimized in a fast way in a half quadratic form. Experimental results demonstrate that the proposed approach successfully separates the reflection layer in several real black box videos.