4.7 Article

Ultrametrics for context-aware comparison of binary images

Related references

Note: Only part of the references are listed.
Article Computer Science, Artificial Intelligence

Multispectral and hyperspectral image fusion in remote sensing: A survey

Gemine Vivone

Summary: The fusion of multispectral and hyperspectral images, aiming to combine high spatial resolution MS images with HS data showing a lower spatial resolution but a more accurate spectral resolution, has gained significant attention. This survey provides a comprehensive review of the subject and classifies the related approaches into three categories: pansharpening-based, decomposition-based, and machine learning-based. It also discusses widely used datasets, performance assessment, open issues, and future research directions.

INFORMATION FUSION (2023)

Article Computer Science, Artificial Intelligence

Multi-level multi-type self-generated knowledge fusion for cardiac ultrasound segmentation

Chengjin Yu et al.

Summary: Most existing methods for cardiac echocardiography segmentation require a large number of labeled data, which is time-consuming and laborious for physicians. In this study, we propose a fusion method of multi-level and multi-type self-generated knowledge to address this challenge. We extract multi-level sub-anatomical structure information from ultrasound images using a superpixel method, and then fuse various types of information generated by multiple pretext tasks. The experimental results demonstrate the effectiveness of our method in echocardiography segmentation task, achieving comparable performance to fully supervised methods without requiring a high amount of labeled data.

INFORMATION FUSION (2023)

Article Environmental Sciences

Consensus Techniques for Unsupervised Binary Change Detection Using Multi-Scale Segmentation Detectors for Land Cover Vegetation Images

F. Javier Cardama et al.

Summary: In this study, the change detection problem in very-high-spatial-resolution remote sensing images was investigated, focusing on the vegetation corresponding to crops and natural ecosystems. A consensus multi-scale binary change detection technique based on object-based features extraction was developed to address the challenge of similar spectral signatures of vegetation elements. Different detectors based on various segmentation algorithms were utilized at different scales to capture changes at different granularity levels. The proposed approach, including the use of CVA-SAM at the segment level, demonstrated effectiveness in identifying changes over land cover vegetation images with different types, spatial and spectral resolutions.

REMOTE SENSING (2023)

Article Computer Science, Artificial Intelligence

Causal knowledge fusion for 3D cross-modality cardiac image segmentation

Saidi Guo et al.

Summary: In this paper, we propose the causal knowledge fusion (CKF) framework to solve the challenge of 3D cross-modality cardiac image segmentation. The CKF explores causal intervention to obtain the anatomical factor and discards the modality factor, improving the information fusion and spatial learning ability. Experimental results show that the CKF is effective and superior to state-of-the-art segmentation methods.

INFORMATION FUSION (2023)

Proceedings Paper Computer Science, Theory & Methods

Boundary-aware Image Inpainting with Multiple Auxiliary Cues

Yohei Yamashita et al.

Summary: Image inpainting is a technique used to remove foreground objects from an image and restore the background pixels. This paper proposes a new method that uses depth images as auxiliary cues, and experiments show that it outperforms the baseline method both quantitatively and qualitatively.

2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW 2022 (2022)

Article Computer Science, Artificial Intelligence

Image fusion meets deep learning: A survey and perspective

Hao Zhang et al.

Summary: Image fusion aims to extract and combine meaningful information from different source images to generate a single informative image. The development of deep learning, with techniques like generative adversarial networks and autoencoders, has significantly advanced image fusion. However, a comprehensive review of the latest deep-learning methods in different fusion scenarios is lacking, which is addressed in this survey.

INFORMATION FUSION (2021)

Article Computer Science, Artificial Intelligence

Sugeno integral generalization applied to improve adaptive image binarization

Francesco Bardozzo et al.

Summary: This paper introduces a new adaptive binarization technique FLAT based on fuzzy integral images, as well as new generalizations of different fuzzy integrals and a modified design of SAT. Experimental results demonstrate that the proposed methodology produces better thresholds than other global and local thresholding algorithms.

INFORMATION FUSION (2021)

Article Computer Science, Artificial Intelligence

SoftSeg: Advantages of soft versus binary training for image segmentation

Charley Gros et al.

Summary: SoftSeg is a deep learning training approach that utilizes soft ground truth labels, not limited to binary predictions. By avoiding binarization, using normalized ReLU activation layer, and regression loss function, SoftSeg outperforms traditional approaches in MRI segmentation tasks, especially in terms of sensitivity to small objects.

MEDICAL IMAGE ANALYSIS (2021)

Article Computer Science, Interdisciplinary Applications

Reducing the Hausdorff Distance in Medical Image Segmentation With Convolutional Neural Networks

Davood Karimi et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2020)

Article Computer Science, Artificial Intelligence

MultiResUNet : Rethinking the U-Net architecture for multimodal biomedical image segmentation

Nabil Ibtehaz et al.

NEURAL NETWORKS (2020)

Article Computer Science, Artificial Intelligence

Deep feature fusion through adaptive discriminative metric learning for scene recognition

Chen Wang et al.

INFORMATION FUSION (2020)

Article Computer Science, Artificial Intelligence

Scene analysis and search using local features and support vector machine for effective content-based image retrieval

Uzma Sharif et al.

ARTIFICIAL INTELLIGENCE REVIEW (2019)

Article Computer Science, Artificial Intelligence

Superpixel-Based Fast Fuzzy C-Means Clustering for Color Image Segmentation

Tao Lei et al.

IEEE TRANSACTIONS ON FUZZY SYSTEMS (2019)

Article Geochemistry & Geophysics

A Generalized Distance Transform: Theory and Applications to Weather Analysis and Forecasting

Dominique Brunet et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2017)

Article Biology

Modelling three-dimensional fungal growth in response to environmental stimuli

G. Vidal-Diez de Ulzurrun et al.

JOURNAL OF THEORETICAL BIOLOGY (2017)

Article Computer Science, Artificial Intelligence

Separability Criteria for the Evaluation of Boundary Detection Benchmarks

C. Lopez-Molina et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2016)

Review Computer Science, Artificial Intelligence

A review of remote sensing image fusion methods

Hassan Ghassemian

INFORMATION FUSION (2016)

Article Computer Science, Artificial Intelligence

Twofold consensus for boundary detection ground truth

C. Lopez-Molina et al.

KNOWLEDGE-BASED SYSTEMS (2016)

Article Neurosciences

A systematic comparison between visual cues for boundary detection

David A. Mely et al.

VISION RESEARCH (2016)

Article Computer Science, Artificial Intelligence

Regularized local metric learning for person re-identification

Venice Erin Liong et al.

PATTERN RECOGNITION LETTERS (2015)

Article Radiology, Nuclear Medicine & Medical Imaging

Metrics for evaluating 3D medical image segmentation: analysis, selection, and tool

Abdel Aziz Taha et al.

BMC MEDICAL IMAGING (2015)

Article Computer Science, Artificial Intelligence

Unsupervised edge map scoring: A statistical complexity approach

Javier Gimenez et al.

COMPUTER VISION AND IMAGE UNDERSTANDING (2014)

Article Mathematics

ROUNDNESS PROPERTIES OF ULTRAMETRIC SPACES

Timothy Faver et al.

GLASGOW MATHEMATICAL JOURNAL (2014)

Article Computer Science, Artificial Intelligence

Image Fusion with Guided Filtering

Shutao Li et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2013)

Article Computer Science, Artificial Intelligence

Quantitative error measures for edge detection

C. Lopez-Molina et al.

PATTERN RECOGNITION (2013)

Article Computer Science, Artificial Intelligence

Context-Aware Saliency Detection

Stas Goferman et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2012)

Article Computer Science, Interdisciplinary Applications

Robust Statistical Label Fusion Through Consensus Level, Labeler Accuracy, and Truth Estimation (COLLATE)

Andrew J. Asman et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2011)

Article Computer Science, Artificial Intelligence

Contour Detection and Hierarchical Image Segmentation

Pablo Arbelaez et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2011)

Review Computer Science, Artificial Intelligence

Edge and line oriented contour detection: State of the art

Giuseppe Papari et al.

IMAGE AND VISION COMPUTING (2011)

Article Computer Science, Artificial Intelligence

Image segmentation algorithm development using ground truth image data sets

Daniel Crevier

COMPUTER VISION AND IMAGE UNDERSTANDING (2008)

Article Computer Science, Artificial Intelligence

Automatic generation of consensus ground truth for the comparison of edge detection techniques

N. L. Fernandez-Garcia et al.

IMAGE AND VISION COMPUTING (2008)

Article Computer Science, Artificial Intelligence

Toward objective evaluation of image segmentation algorithms

Ranjith Unnikrishnan et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2007)

Article Engineering, Biomedical

A framework for evaluating image segmentation algorithms

JK Udupa et al.

COMPUTERIZED MEDICAL IMAGING AND GRAPHICS (2006)

Article Computer Science, Interdisciplinary Applications

Simultaneous truth and performance level estimation (STAPLE): An algorithm for the validation of image segmentation

SK Warfield et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2004)

Article Computer Science, Artificial Intelligence

Learning to detect natural image boundaries using local brightness, color, and texture cues

DR Martin et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2004)

Article Computer Science, Artificial Intelligence

A method for objective edge detection evaluation and detector parameter selection

Y Yitzhaky et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2003)

Article Computer Science, Artificial Intelligence

Shape matching and object recognition using shape contexts

S Belongie et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2002)

Article Mathematics, Applied

Metrics and T-equalities

B De Baets et al.

JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS (2002)