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Fast computation of a contrast-invariant image representation
1CMLA, Ecole Normale Supérieure de Cachan, 94235 Cachan Cedex, France. monasse@cmla.ens-cachan.fr
Summary
This study introduces a novel, contrast-independent image representation using a tree of shapes derived from level sets. This method offers a complete and non-redundant way to analyze images, detailed with a fast algorithm for computation.
Area of Science:
- Computer Vision
- Image Processing
- Mathematical Morphology
Background:
- Traditional image representations are often sensitive to variations in contrast.
- A need exists for robust image analysis techniques that are invariant to illumination and contrast changes.
- Existing methods may lack completeness or redundancy in image decomposition.
Purpose of the Study:
- To introduce a novel, contrast-independent image representation.
- To develop a method for decomposing images into a tree of shapes.
- To present a fast algorithm for computing this representation.
Main Methods:
- Image decomposition based on connected components of level sets.
- Construction of a tree structure representing image shapes.
- Detailed explanation of the fast level lines transform (FLLT) algorithm.
Main Results:
- A full and non-redundant image representation is achieved.
- The proposed representation is independent of image contrast.
- A computationally efficient algorithm (FLLT) for generating the representation is presented.
Conclusions:
- The novel shape-based image representation offers robustness against contrast variations.
- The fast level lines transform provides an efficient method for image analysis.
- The representation has potential for various direct applications in image processing.
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