Discrete wavelet for multifractal texture classification: application to medical ultrasound imaging - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2010

Discrete wavelet for multifractal texture classification: application to medical ultrasound imaging

Résumé

This paper deals with multifractal characterization of skin cancer in ultrasound images. The proposed method establishes a multifractal analysis framework of such images based on a new multiresolution indicator, called the maximum wavelet coefficient, derived from the wavelet leaders. Two main contributions are brought up: first, it proposes a method for the estimation of multifractal features. Second, it reveals the potential of multifractal features to characterize skin melanoma. In order to study the efficiency of our maximum coefficient estimator, we compare its results on a simulated image against wavelet leaders based estimator. We then apply the approach on various samples from different skin images. Results show that the extracted features make a promising quantitative indicator to distinguish between different tissues.
Fichier principal
Vignette du fichier
Discrete wavelet for multifractal texture classification_application to medical ultrasound imaging.pdf (494.87 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03149774 , version 1 (26-02-2021)

Identifiants

Citer

Meriem Djeddi, Abdeldjalil Ouahabi, Hadj Batatia, Adrian Basarab, Denis Kouamé. Discrete wavelet for multifractal texture classification: application to medical ultrasound imaging. IEEE International Conference on Image Processing (ICIP 2010), IEEE Signal Processing Society, Sep 2010, Hong Kong, China. pp.637--640, ⟨10.1109/ICIP.2010.5650017⟩. ⟨hal-03149774⟩
59 Consultations
80 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More