Bias Image Correction Via Stationarity Maximization - Archive ouverte HAL Accéder directement au contenu
Chapitre D'ouvrage Année : 2007

Bias Image Correction Via Stationarity Maximization

Résumé

Automated acquisitions in microscopy may come along with strong illumination artifacts due to poor physical imaging conditions. Such artifacts obviously have direct consequences on the efficiency of an image analysis algorithm and on the quantitative measures. In this paper, we propose a method to correct illumination artifacts on biological images. This correction is based on orthogonal polynomial modeling, combined with stationary maximization criteria. To validate the proposed method we show that we improve particle detection algorithm.

Dates et versions

hal-02901994 , version 1 (15-08-2020)

Identifiants

Citer

T. Dorval, Arnaud Ogier, Auguste Genovesio. Bias Image Correction Via Stationarity Maximization. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007, 4792, Springer Berlin Heidelberg; Springer Berlin Heidelberg, pp.693-700, 2007, Lecture Notes in Computer Science, ⟨10.1007/978-3-540-75759-7_84⟩. ⟨hal-02901994⟩
20 Consultations
1 Téléchargements

Altmetric

Partager

Gmail Mastodon Facebook X LinkedIn More