Robust video denoising for better subjective evaluation

Abstract

Video denoising is a pre-processing step of many high level video processing applications since it can considerably enhance the perceived video quality, increase compression effectiveness, facilitate transmission bandwidth reduction and improve the performance of the subsequent higher level task such as feature extraction, object detection, prediction, coding and object tracking. In this paper, a new scheme for video denoising based on spatial filtering is proposed which synthesizes the blurring caused by averaging filter and sharpening due to high boost filter for effective objective and subjective video quality enhancement. The main drawback of averaging filter is that it gives a blurring effect and de-emphasizes the fine details from an image such as edges and texture. This blurring artefact is compensated through highboost filtering operation by selecting an appropriate value of the highboost weight factor intended for better video quality and superior HVS performance. Experimental results show that the proposed method achieves better performance of noise removal with much reduced blurring and fine detail preservation in terms of improved objective and subjective video quality.Keywords-Image and video processing; Video denoising; spatial averaging filter; highboost filter; human visual system (HVS); subjective evaluation; additive white Gaussian noise.

New approach for noise cleaning on real time videos based low-pass filtering and mathimatical morphology

“…M. Ghoniem, has integrated temporal and spatial coordinate of the successive images to develop a spatiotemporal regularization on weighted graphs [6]. A. Acharya combined high boost filter with soft filter for video de-noising with preserving fines detail of the processed objects [1]. Many other techniques combine wavelet spatial de-noising and temporal filtering.…”