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In this paper, we propose a novel image quality assessment (IQA) metric based on nonnegative matrix factorization (NM-F). With nonnegativity and parts-based properties, NMF well demonstrates how human brain learns the parts of objects. This makes NMF distinguished from other feature extraction methods like singular value decomposition (SVD), principal components analysis (PCA), etc. Inspired by this,...
For high-quality image rendering using Monte Carlo methods, a large number of samples are required to be computed for each pixel. Adaptive sampling aims to decrease the total number of samples by concentrating samples on difficult regions. However, existing adaptive sampling schemes haven't fully exploited the potential of image regions with complex structures to the reduction of sample numbers. To...
Although wireless sensor networks (WSNs) are powerful in monitoring physical events, the data collected from a WSN are almost always incomplete if the surveyed physical event spreads over a wide area. The reason for this incompleteness is twofold: i) insufficient network coverage and ii) data aggregation for energy saving. Whereas the existing recovery schemes only tackle the second aspect, we develop...
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