Task-Based Evaulation of Image Filtering within a Class of Geometry-Driven-Diffusion Algorithms

Ivan Bajla, Igor Holländer, Viktor Witkovsky

Publikation: Beitrag in Buch oder TagungsbandBuchkapitel

Abstract

A novel task-based algorithm performance evaluation technique is propose for the evaluation of geometry-driven diffusion (GDD) methods used for increasing the signal-to-noise ratio in MR tomograms. It is based on a probabilistic model of stepwise constant image corrupted the distribution parameters of the ran-dom variable derived from intensity gradient are used for characterization of staircase image artifacts in diffused images. The proposed evaluation tech-nique incorporates a "gold standard" of the GDD algorithms, defined as a dif-fusion process governed by ideal values of conductance
OriginalspracheEnglisch
Titelerschienen in: Empirical Evaluation Methods in Computer Vision. Series in machine perception and artificial intelligence. Ed. by: Christensen Henrik I.
Seiten89-115
Seitenumfang27
PublikationsstatusVeröffentlicht - 2002

Research Field

  • Nicht definiert

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