Cost-effective video filtering solution for real-time vision systems
EURASIP Journal on Applied Signal Processing
Phase information and space filling curves in noisy motion estimation
IEEE Transactions on Image Processing
Advanced film grain noise extraction and synthesis for high-definition video coding
IEEE Transactions on Circuits and Systems for Video Technology
Fast Multi-Hypothesis Motion Compensated Filter for Video Denoising
Journal of Signal Processing Systems
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A novel spatio-temporal filter is described for monochrome image sequences with either signal-independent or signal-dependent noise by considering both spatial and temporal correlations. With the assumptions of spatio-temporal separability and temporal stationarity, it is shown that motion-compensated groups of frames can be decorrelated by using the Karhunen-Loeve transform. Practical filters that work well on a variety of image sequences are developed by first applying the Hadamard transform along the temporal direction. Subsequently, the parametric adaptive Wiener filter is applied to each of the resulting approximately decorrelated transformed images. These transformed images are classified into one average image and a remaining set of residual images, which provide interesting and useful interpretations of the type of image sequence. The filter performance is evaluated by considering different types of image sequences in the database. The procedure advanced for processing a sequence of monochrome images can be adapted for generalization to multispectral images and this possibility is currently under detailed investigation