A Novel Approach for Denoising and Enhancement of Extremely Low-light Video
Abstract— a novel approach for noise reduction and enhancement of extremely low-light video is
proposed. For noise removal, a motion adaptive temporal filtering based on a Kalman structured updating is presented.
Dynamic range of denoised video is increased by adjustment of RGB histograms using Gamma correction with adaptive
clipping thresholds. Finally, residual noise is removed using a nonlocal means (NLM) denoising filter. The proposed method works directly on the color filter array (CFA) raw video for achieving low memory consumption< final year projects >