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Distributed compressive sensing is a framework considering jointly sparsity within signal ensembles along with multiple measurement vectors (MMVs). The current theoretical bound of performance for MMVs, however, is derived to be the same with that for single MV (SMV) because the characteristics of signal ensembles are ignored. In this work, we introduce a new factor called "Euclidean distances...
In this paper, we propose a new divide-and-conquer based method, called fusion of multiple binary age-grouping-estimation systems, for human facial age estimation. Under a specific constraint, such as a given facial feature or classification/regression method, what is the better framework for age estimation? First we employ multiple binary-grouping systems for age group classification. Each face image...
Instantaneous frequency attractors (IFAs), obtained from the phase of a time-frequency representation, have been introduced for instantaneous frequency (IF) estimation. In this paper, another kind of attractors called group delay attractors (GDAs) are proposed to improve the IFA-based method. The GDAs can reveal IFs which cannot be estimated from the IFAs. Simulation results show that the IF estimation...
In this paper, an improved color constancy approach is presented by considering the disadvantage of the well-known max-RGB algorithm: Only the unreliable maximum intensities are taken for illuminant estimation. To solve this problem, we propose the chromaticity neutralization process, which selects the representative pixels for robust illuminant computing. Moreover, to deal with the color deviation...
Security is still a relatively unexplored issue in image hashing. In this paper, we address this problem and present a new metric, called minimum distortion estimation (MDE), by demonstrating its appropriateness over entropy for secure hashing evaluation. We investigate the relationship between bit changing rate and content distortion via statistical analyses of MDE. This provides a guideline for...
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