A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pyramid-based texture analysis/synthesis
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Prior Learning and Gibbs Reaction-Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Filters, Random Fields and Maximum Entropy (FRAME): Towards a Unified Theory for Texture Modeling
International Journal of Computer Vision
Filtering for Texture Classification: A Comparative Study
IEEE Transactions on Pattern Analysis and Machine Intelligence
Histogram clustering for unsupervised segmentation and image retrieval
Pattern Recognition Letters
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Parametric Texture Model Based on Joint Statistics of Complex Wavelet Coefficients
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: modeling, learning, sampling and computing, Part I
The Earth Mover's Distance as a Metric for Image Retrieval
International Journal of Computer Vision
General Scheme of Region Competition Based on Scale Space
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Segmentation by Data-Driven Markov Chain Monte Carlo
IEEE Transactions on Pattern Analysis and Machine Intelligence
Equivalence of Julesz Ensembles and FRAME Models
International Journal of Computer Vision - Special issue on Genomic Signal Processing
Geodesic Active Regions and Level Set Methods for Supervised Texture Segmentation
International Journal of Computer Vision
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
International Journal of Computer Vision
Universal Analytical Forms for Modeling Image Probabilities
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
DCC '97 Proceedings of the Conference on Data Compression
Gradient flows and geometric active contour models
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
The steerable pyramid: a flexible architecture for multi-scale derivative computation
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 3)-Volume 3 - Volume 3
Empirical Evaluation of Dissimilarity Measures for Color and Texture
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Fragmentation in the Vision of Scenes
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Binary Partitioning, Perceptual Grouping, and Restoration with Semidefinite Programming
IEEE Transactions on Pattern Analysis and Machine Intelligence
Spectral Grouping Using the Nyström Method
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image compression via joint statistical characterization in the wavelet domain
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Image subband coding using arithmetic coded trellis coded quantization
IEEE Transactions on Circuits and Systems for Video Technology
A Multiphase Dynamic Labeling Model for Variational Recognition-driven Image Segmentation
International Journal of Computer Vision
Hypotheses for Image Features, Icons and Textons
International Journal of Computer Vision
Three-Dimensional Shape Knowledge for Joint Image Segmentation and Pose Tracking
International Journal of Computer Vision
Detecting defects with image data
Computational Statistics & Data Analysis
Journal of Mathematical Imaging and Vision
From Inpainting to Active Contours
International Journal of Computer Vision
Extracting Grain Boundaries and Macroscopic Deformations from Images on Atomic Scale
Journal of Scientific Computing
International Journal of Computer Vision
Mumford-Shah regularizer with contextual feedback
Journal of Mathematical Imaging and Vision
Preferential image segmentation using trees of shapes
IEEE Transactions on Image Processing
Analysis of Numerical Methods for Level Set Based Image Segmentation
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
On the statistical interpretation of the piecewise smooth Mumford-Shah functional
SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
Identification of grain boundary contours at atomic scale
SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
Image statistics and local spatial conditions for nonstationary blurred image reconstruction
Proceedings of the 29th DAGM conference on Pattern recognition
Novel classification and segmentation techniques with application to remotely sensed images
Transactions on rough sets VII
Image segmentation by MAP-ML estimations
IEEE Transactions on Image Processing
Non-local characterization of scenery images: statistics, 3D reasoning, and a generative model
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
VLSM'05 Proceedings of the Third international conference on Variational, Geometric, and Level Set Methods in Computer Vision
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We integrate a model for filter response statistics of natural images into a variational framework for image segmentation. Incorporated in a sound probabilistic distance measure, the model drives level sets toward meaningful segmentations of complex textures and natural scenes. Despite its enhanced descriptive power, our approach preserves the efficiency of level set based segmentation since each region comprises two model parameters only. Analyzing thousands of natural images we select suitable filter banks, validate the statistical basis of our model, and demonstrate that it outperforms variational segmentation methods using second-order statistics.