A Wong

Publications (2)6.08 Total impact

• Article: A Bayesian Theoretic Approach to Multiscale Complex-Phase-Order Representations

  A. Wong
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  ABSTRACT: This paper explores a Bayesian theoretic approach to constructing multiscale complex-phase-order representations. We formulate the construction of complex-phase-order representations at different structural scales based on the scale-space theory. Linear and nonlinear deterministic approaches are explored, and a Bayesian theoretic approach is introduced for constructing representations in such a way that strong structure localization and noise resilience are achieved. Experiments illustrate its potential for constructing robust multiscale complex-phase-order representations with well-localized structures across all scales under high-noise situations. Illustrative examples of applications of the proposed approach is presented in the form of multimodal image registration and feature extraction.
  IEEE Transactions on Image Processing 02/2012; · 3.04 Impact Factor
• Article: A Bayesian theoretic approach to multiscale complex-phase-order representations.

  Alexander Wong
  [show abstract] [hide abstract]
  ABSTRACT: This paper explores a Bayesian theoretic approach to constructing multiscale complex-phase-order representations. We formulate the construction of complex-phase-order representations at different structural scales based on the scale-space theory. Linear and nonlinear deterministic approaches are explored, and a Bayesian theoretic approach is introduced for constructing representations in such a way that strong structure localization and noise resilience are achieved. Experiments illustrate its potential for constructing robust multiscale complex-phase-order representations with well-localized structures across all scales under high-noise situations. Illustrative examples of applications of the proposed approach is presented in the form of multimodal image registration and feature extraction.
  IEEE Transactions on Image Processing 06/2011; 21(1):28-40. · 3.04 Impact Factor