A Novel Approach for Denoising and Enhancement of Extremely Low-light Video
Abstract: A Novel Approach for Denoising and enhancement of extremely low-light video is proposed. For noise removal, a motion adaptive temporal filtering based on 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 < Final Year Projects 2016 > denoising filter. The proposed method works directly on the color filter array raw video for achieving low memory consumption.To capture images of high dynamic range, most consumer cameras often rely on automatic exposure control, but longer exposure time results motion blur. Secondly, image sequences captured in low-light conditions often have very low signal-to-noise ratio (SNR).
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