Results 131 to 140 of about 495 (155)
Multiscale superpixel classification for tumor segmentation in breast ultrasound images
2012 19th IEEE International Conference on Image Processing, 2012 Tumor localization and segmentation in breast ultrasound (BUS) images is an important as well as intractable problem for computer-aided diagnosis (CAD) due to the high variation in shape and appearance. We propose a novel algorithm in this paper without making any assumption on tumor, compared to most previous works.
Zhihui Hao +5 more
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Neurocomputing, 2020
Abstract Sparse representation and dictionary learning have been successfully applied in hyperspectral image classification. Generally, it is more effective to learn the sub-dictionary for each class and utilize multiple scale strategy. However, the sub-dictionary may only consider the within-class information and ignore the discriminative ...
Xiaobo Shen, Peng Fu, Quansen Sun
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Abstract Sparse representation and dictionary learning have been successfully applied in hyperspectral image classification. Generally, it is more effective to learn the sub-dictionary for each class and utilize multiple scale strategy. However, the sub-dictionary may only consider the within-class information and ignore the discriminative ...
Xiaobo Shen, Peng Fu, Quansen Sun
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Fast Multiscale Superpixel Segmentation for SAR Imagery
IEEE Geoscience and Remote Sensing Letters, 2022Deliang Xiang, Yi Su
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IEEE Geoscience and Remote Sensing Letters, 2017
This letter introduces a new spectral–spatial classification method for hyperspectral images. A multiscale superpixel segmentation is first used to model the distribution of classes based on spatial information. In this context, the original hyperspectral image is integrated with segmentation maps via a feature fusion process in different scales such ...
Haoyang Yu, Lianru Gao, Wenzhi Liao
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This letter introduces a new spectral–spatial classification method for hyperspectral images. A multiscale superpixel segmentation is first used to model the distribution of classes based on spatial information. In this context, the original hyperspectral image is integrated with segmentation maps via a feature fusion process in different scales such ...
Haoyang Yu, Lianru Gao, Wenzhi Liao
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Multiscale superpixel-based fusion framework for hyperspectral image classification
2018 Fifth International Workshop on Earth Observation and Remote Sensing Applications (EORSA), 2018 Since it is usually difficult and time-consuming to obtain sufficient labeled samples in practice, the samll number of sample is one of the challenging issue for hyperspectral image classifiction. Fortunately, due to the spatial correlation of the surface of the materials, it is feasible to improve classification performance from the perspective of ...
Sen Jia, Xianglong Deng, Kuilin Wu
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Multiscale superpixel method for segmentation of breast ultrasound
Computers in Biology and Medicine, 2020In medical diagnostics, breast ultrasound is an inexpensive and flexible imaging modality. The segmentation of breast ultrasounds to identify tumour regions is a challenging and complex task. The major problems of effective tumour identification are speckle noise, artefacts and low contrast.
Ademola Enitan Ilesanmi +2 more
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PolSAR Image Classification With Multiscale Superpixel-Based Graph Convolutional Network
IEEE Transactions on Geoscience and Remote Sensing, 2022Convolutional neural networks (CNNs) have demonstrated impressive ability to achieve promising results in PolSAR image classification. However, the traditional CNN performs convolution on local square regions with fixed sizes. The selection of these local square regions (patches) cannot fully take advantage of the boundary information of land covers ...
Jianda Cheng +4 more
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Human body segmentation in a static image with multiscale superpixels
2011 3rd International Conference on Awareness Science and Technology (iCAST), 2011In this work, we propose a new method for human body accurate detection in a static image with multiscale superpixels. The main contribution of this work is as follows: (1) A new framework for human body accurate detection using multiscale superpixels and classifier with autothreshold is proposed. (2) Some effective constraints for human body detection
Meng Yao, Huchuan Lu
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HUMAN BODY SEGMENTATION IN A STATIC IMAGE WITH ON-LINE ADABOOST AT MULTISCALE SUPERPIXELS
International Journal of Image and Graphics, 2012In this work, we propose a new method for accurate human body detection in a static image with multi-scale superpixels based on two models. First, based on the face detection, we use designed torso part model to estimate the torso part region to provide the positive samples of on-line AdaBoost.
Shifeng Li, Meng Yao, Huchuan Lu
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Multiscale superpixel segmentation-based band expansion for change detection
Remote Sensing Letters, 2023Change detection (CD) for remotely sensed images has gained great relevance in the last decade due to an increase in the number of Earth Observation (EO) missions, improved temporal resolutions, and open data policies. However, efficient exploitation and integration of spatial information for CD remains a challenging issue.
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