Temporal-Spatial Filtering for Enhancement of Low-Light Surveillance Video
Fan Guo, Jin Tang, Hui Peng, and Beiji Zou†
School of Information Science and Engineering, Central South University
Changsha, Hunan 410083, China
A new surveillance video enhancement method is proposed to improve the visual effect of videos captured in low-light conditions. The proposed technique, called temporal-spatial (TS) filtering, uses adaptive temporal filtering and nonlocal mean filtering to smooth the transmission map in the temporal and spatial dimensions and thus yields restored video sequences with significantly reduced noise, improved details and good spatial and temporal coherence. The main advantage of this work is that the performance of contrast enhancement, noise reduction and temporal-spatial coherence can be significantly improved using the proposed framework, which adopts a strategy that applies the same transmission map to a series of video frames. Comparative study and quantitative evaluation demonstrate that the proposed method is better than previous techniques in terms of reducing noise and improving contrast.
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