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Statistical Principles in Image Modeling

Summary: [This abstract is based on the authors’ abstract.] Natural scenes present a rich variety of visual patterns, and in order to recognize these patterns, statistical models must be constructed. Three statistical principles for modeling image patterns are described: the sparse coding principle, the minimax entropy principle, and the meaningful alignment principle. These principles and their relationships in the context of modeling images correspond to three regimes of composition patterns of Gabor wavelets which are connected by changes in scale or resolution.

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  • Topics: Statistics
  • Keywords: Imaging, Entropy, Alignment, Computer-Aided Design (CAD), Statistical methods, Imaging
  • Author: Wu, Ying Nian; Li, Jinhui; Liu, Ziqiang; Zhu, Song-Chun
  • Journal: Technometrics