Robust Visual Enhancement of Moving Contents in Projected Imagery

For any projection system, one goal will surely be to maximize the quality of projected imagery at a minimized hardware cost, which is considered a challenging engineering problem. Experience in applying different image filters and enhancements to projected video suggests quite clearly that the quality of a projected enhanced video is very much a function of the content of the video itself; that is, to first order, whether the video contains content which is moving as opposed to still, since the human visual system tolerates much more blur in moving imagery. We would therefore assert that the moving and non-moving pixels of a given video stream should be enhanced differently, using class-dependent video enhancement filters to achieve maximum visual quality. In this paper, we introduce such a novel motion--dependent content enhancement scheme, based on a pixel-wise moving / non-moving classification, with the actual enhancement obtained via class--dependent Wiener deconvolution filtering. Experimental results on four challenging videos show that the proposed scheme offers improved visual quality.