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Antiextensive connected operators for image and sequence processing.

P Salembier1, A Oliveras, L Garrido

  • 1E.T.S.E.T.B., Univ. Politecnica de Catalunya, Barcelona. philippe@gps.tsc.upc.es

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 16, 2008
PubMed
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This study introduces connected operators for image filtering, preserving contour information by merging flat zones. Novel generalizations enhance texture analysis and reduce signal leakage, offering efficient solutions.

Area of Science:

  • Image processing
  • Computer vision
  • Mathematical morphology

Background:

  • Connected operators are valuable for image filtering due to their ability to preserve contour information by merging flat zones.
  • Traditional connected operators have limitations in handling texture and can exhibit significant signal leakage.

Purpose of the Study:

  • To present a structured representation, the max-tree, for efficient processing of antiextensive connected operators.
  • To generalize connected operators for improved texture analysis and reduced leakage.
  • To explore simplification criteria and efficient algorithmic solutions for operator implementation.

Main Methods:

  • Utilizing the max-tree as a structured representation for connected operator processing.
  • Analyzing and modifying connectivity definitions to incorporate texture handling.

Related Experiment Videos

  • Developing simplification criteria (simplicity, entropy, motion) for operator design.
  • Formulating the non-increasing criterion problem as an optimization solvable by the Viterbi algorithm.

    • Main Results:

    • Demonstrated that connected operators implicitly operate on a structured representation of flat zones.
    • Introduced generalized connected operators capable of handling texture and reducing leakage.
    • Proposed simplification criteria leading to specialized operators.
    • Showcased efficient implementation strategies for these operators.

    Conclusions:

    • The max-tree provides an efficient structure for antiextensive connected operators.
    • Generalizations of connected operators enhance their applicability to complex image data, including textures.
    • The proposed methods allow for efficient and optimized implementation of advanced connected operators.