A morphological pyramidal image decomposition

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Abstract

A multiresolution image representation is presented in which iterative morphological filters of many scales but identical shape serve as basis functions. Structural pattern decomposition is achieved by subtracting successive layers in the multiresolution representation. The representation differs from established techniques in that the code elements have a well defined location and size. The resulting image description provides a useful basis for multiresolution shape analysis and is well suited for VLSI implementation.

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    Citation Excerpt :

    TDB methods are mainly based on the multi-scale transform (MST), which contain three steps: performing a given MST, fusing the coefficients based on specific rules, and reconstructing the fused result using the corresponding inverse MST. Typical MST tools include the Laplacian pyramid transform [6], morphological pyramid transform [7], discrete wavelet transform [8], double complex tree wavelet transform [9], contourlet transform (CT) [10], non-subsampled contourlet transform (NSCT) [11,12], and non-subsampled shearlet transform (NSST) [13]. Du et al. [14] developed a local energy maximization and information-of-interest-based method using the local Laplacian filter domain.

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