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Regularized, fast, and robust analytical Q-ball imaging.
We propose a regularized, fast, and robust analytical solution for the Q-ball imaging (QBI) reconstruction of the orientation distribution function (ODF) together with its detailed validation and aExpand
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Vector-valued image regularization with PDEs: a common framework for different applications
In this paper, we focus on techniques for vector-valued image regularization, based on variational methods and PDE. Starting from the study of PDE-based formalisms previously proposed in theExpand
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A Robust Technique for Matching two Uncalibrated Images Through the Recovery of the Unknown Epipolar Geometry
Abstract This paper proposes a robust approach to image matching by exploiting the only available geometric constraint, namely, the epipolar constraint. The images are uncalibrated, namely the motionExpand
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Using Canny's criteria to derive a recursively implemented optimal edge detector
  • R. Deriche
  • Computer Science
  • International Journal of Computer Vision
  • 1 June 1987
A highly efficient recursive algorithm for edge detection is presented. Using Canny's design [1], we show that a solution to his precise formulation of detection and localization for an infiniteExpand
  • 1,105
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A Review of Statistical Approaches to Level Set Segmentation: Integrating Color, Texture, Motion and Shape
Since their introduction as a means of front propagation and their first application to edge-based segmentation in the early 90’s, level set methods have become increasingly popular as a generalExpand
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Deterministic and Probabilistic Tractography Based on Complex Fibre Orientation Distributions
We propose an integral concept for tractography to describe crossing and splitting fibre bundles based on the fibre orientation distribution function (ODF) estimated from high angular resolutionExpand
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Geodesic Active Contours and Level Sets for the Detection and Tracking of Moving Objects
This paper presents a new variational framework for detecting and tracking multiple moving objects in image sequences. Motion detection is performed using a statistical framework for which theExpand
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Geodesic Active Regions and Level Set Methods for Supervised Texture Segmentation
This paper presents a novel variational framework to deal with frame partition problems in Computer Vision. This framework exploits boundary and region-based segmentation modules under a curve-basedExpand
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Vector-valued image regularization with PDE's: a common framework for different applications
We address the problem of vector-valued image regularization with variational methods and PDEs. From the study of existing formalisms, we propose a unifying framework based on a very localExpand
  • 264
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A variational framework for active and adaptative segmentation of vector valued images
Much effort has been made in integrating different information in a variational framework to segment images. Recent works on curve propagation were able to incorporate stochastic information (seeExpand
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