Early vision: from computational structure to algorithms and parallel hardware
Computer Vision, Graphics, and Image Processing
Regularization of inverse visual problems involving discontinuities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Picture Segmentation by a Tree Traversal Algorithm
Journal of the ACM (JACM)
Computer Vision
Structured Computer Vision; Machine Perception through Hierarchical Computation Structures
Structured Computer Vision; Machine Perception through Hierarchical Computation Structures
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
A Multiresolution Hierarchical Approach to Image Segmentation Based on Intensity Extrema
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multidimensional Systems and Signal Processing
Segmenting Images Corrupted by Correlated Noise
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Tractability of Segmentation and Scene Analysis
International Journal of Computer Vision
Isophotes Selection and Reaction-Diffusion Model for Object Boundaries Estimation
International Journal of Computer Vision
Optimal Level Curves and Global Minimizers of Cost Functionals in Image Segmentation
Journal of Mathematical Imaging and Vision
Markov Random Field Models for Unsupervised Segmentation of Textured Color Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Level Lines as Global Minimizers of Energy Functionals in Image Segmentation
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Parallel Multiresolution Image Segmentation with Watershed Transformation
ParNum '99 Proceedings of the 4th International ACPC Conference Including Special Tracks on Parallel Numerics and Parallel Computing in Image Processing, Video Processing, and Multimedia: Parallel Computation
Using connected components to guide image understanding and segmentation
Machine Graphics & Vision International Journal
Energy Partitions and Image Segmentation
Journal of Mathematical Imaging and Vision
Image segmentation based on merging of sub-optimal segmentations
Pattern Recognition Letters
ACM Computing Surveys (CSUR)
Iterative area filtering of multichannel images
Image and Vision Computing
An Efficient Hillclimbing-based Watershed Algorithm and its Prototype Hardware Architecture
Journal of Signal Processing Systems
Annotated Contraction Kernels for Interactive Image Segmentation
GbRPR '09 Proceedings of the 7th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition
Image classification using marginalized kernels for graphs
GbRPR'07 Proceedings of the 6th IAPR-TC-15 international conference on Graph-based representations in pattern recognition
SAR imagery segmentation by statistical region growing and hierarchical merging
Digital Signal Processing
Automatic band selection in multispectral images using mutual information-based clustering
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
Technique for preprocessing of digital mammogram
Computer Methods and Programs in Biomedicine
Multiresolution filtering with application to image segmentation
Mathematical and Computer Modelling: An International Journal
A new parallel tool for classification of remotely sensed imagery
Computers & Geosciences
GeneSIS: A GA-based fuzzy segmentation algorithm for remote sensing images
Knowledge-Based Systems
Hi-index | 0.14 |
A segmentation algorithm based on sequential optimization which produces a hierarchical decomposition of the picture is presented. The decomposition is data driven with no restriction on segment shapes. It can be viewed as a tree, where the nodes correspond to picture segments and where links between nodes indicate set inclusions. Picture segmentation is first regarded as a problem of piecewise picture approximation, which consists of finding the partition with the minimum approximation error. Then, picture segmentation is presented as an hypothesis-testing process which merges only segments that belong to the same region. A hierarchical decomposition constraint is used in both cases, which results in the same stepwise optimization algorithm. At each iteration, the two most similar segments are merged by optimizing a stepwise criterion. The algorithm is used to segment a remote-sensing picture, and illustrate the hierarchical structure of the picture.