Hierarchy in Picture Segmentation: A Stepwise Optimization Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Extensive operators in partition lattices for image sequence analysis
Signal Processing - Video segmentation for content-based processing manipulation
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiresolution-based watersheds for efficient image segmentation
Pattern Recognition Letters
The hierarchy of the cocoons of a graph and its application to image segmentation
Pattern Recognition Letters - Special issue: Graph-based representations in pattern recognition
Multiscale Watershed Segmentation of Multivalued Images
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
EURASIP Journal on Applied Signal Processing
Constrained Connectivity for Hierarchical Image Decomposition and Simplification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multisource images analysis using collaborative clustering
EURASIP Journal on Advances in Signal Processing
Performance measures for object detection evaluation
Pattern Recognition Letters
A causal extraction scheme in top-down pyramids for large images segmentation
SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
Constrained connectivity for the processing of very-high-resolution satellite images
International Journal of Remote Sensing - Spatial Information Retrieval, Analysis, Reasoning and Modelling
Multi-resolution region-based clustering for urban analysis
International Journal of Remote Sensing - Spatial Information Retrieval, Analysis, Reasoning and Modelling
Hierarchical segmentation of multiresolution remote sensing images
ISMM'11 Proceedings of the 10th international conference on Mathematical morphology and its applications to image and signal processing
Antiextensive connected operators for image and sequence processing
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Binary Partition Trees for Object Detection
IEEE Transactions on Image Processing
Spatio-temporal reasoning for the classification of satellite image time series
Pattern Recognition Letters
A hierarchical semantic-based distance for nominal histogram comparison
Data & Knowledge Engineering
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The extraction of urban patterns from very high spatial resolution (VHSR) optical images presents several challenges related to the size, the accuracy and the complexity of the considered data. Based on the availability of several optical images of a same scene at various resolutions (medium, high, and very high spatial resolution), a hierarchical approach is proposed to progressively extract segments of interest from the lowest to the highest resolution data, and then finally determine urban patterns from VHSR images. This approach, inspired by the principle of photo-interpretation, has for purpose to use as much as possible the user's skills while minimising his/her interaction. In order to do so, at each resolution, an interactive segmentation of one sample region is required for each semantic class of the image. Then, the user's behaviour is automatically reproduced in the remainder of the image. This process is mainly based on tree-cuts in binary partition trees. Since it strongly relies on user-defined segmentation examples, it can involve only low level-spatial and radiometric-criteria, then enabling fast computation of comprehensive results. Experiments performed on urban images datasets provide satisfactory results which may be further used for classification purpose.