Results 31 to 40 of about 471,167 (221)
SUPERPIXEL SEGMENTATION FOR POLSAR IMAGES BASED ON HEXAGON INITIALIZATION AND EDGE REFINEMENT [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 Superpixel segmentation for PolSAR images can heavily decrease the number of primitives for subsequent interpretation while reducing the impact of speckle noise.
M. Li +5 more
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Fast Segmentation of Vertebrae CT Image Based on the SNIC Algorithm
Tomography, 2022 Automatic image segmentation plays an important role in the fields of medical image processing so that these fields constantly put forward higher requirements for the accuracy and speed of segmentation.
Bing Li +4 more
doaj +1 more source
Context guided belief propagation for remote sensing image classification. [PDF]
, 2015 We propose a context guided belief propagation (BP) algorithm to perform high spatial resolution multispectral imagery (HSRMI) classification efficiently utilizing superpixel representation.
An, Le, Bhanu, Bir, Mei, Tiancan
core +2 more sources
Remote Sensing, 2022 Convolutional neural networks (CNNs) can extract advanced features of joint spectral–spatial information, which are useful for hyperspectral image (HSI) classification.
Caihong Mu, Z. Dong, Yi Liu
semanticscholar +1 more source
Salient Object Segmentation Based on Superpixel and Background Connectivity Prior
IEEE Access, 2018 Salient object segmentation is well known for detecting and segmenting objects using saliency map as input. In this paper, we propose a salient object segmentation method which integrates saliency, superpixel, and background connectivity prior.
Yuzhen Niu, Chaoran Su, Wenzhong Guo
doaj +1 more source
Sample and Filter: Nonparametric Scene Parsing via Efficient Filtering [PDF]
, 2016 Scene parsing has attracted a lot of attention in computer vision. While parametric models have proven effective for this task, they cannot easily incorporate new training data.
Najafi, Mohammad +3 more
core +2 more sources
COMPARATIVE ANALYSIS OF SUPERPIXEL SEGMENTATION METHODS
International Journal of Engineering Technologies and Management Research, 2020 Superpixel segmentation showed to be a useful preprocessing step in many computer vision applications. Superpixel’s purpose is to reduce the redundancy in the image and increase efficiency from the point of view of the next processing task. This led to a variety of algorithms to compute superpixel segmentations, each with individual strengths and ...
SumitKaur, Dr. R.K Bansal
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Extended set of superpixel features
Компьютерная оптика, 2021 Superpixel-based image processing and analysis methods usually use a small set of superpixel features. Expanding the description of superpixels can improve the quality of processing algorithms. In the paper, a set of 25 basic superpixel features of shape,
A.A. Egorova, V.V. Sergeyev
doaj +1 more source
Remote Sensing, 2022 Hyperspectral image classification (HSIC) methods usually require more training samples for better classification performance. However, a large number of labeled samples are difficult to obtain because it is cost- and time-consuming to label an HSI in a ...
Chunhui Zhao +3 more
doaj +1 more source
Texture-Aware Superpixel Segmentation [PDF]
2019 IEEE International Conference on Image Processing (ICIP), 2019 Most superpixel algorithms compute a trade-off between spatial and color features at the pixel level. Hence, they may need fine parameter tuning to balance the two measures, and highly fail to group pixels with similar local texture properties. In this paper, we address these issues with a new Texture-Aware SuperPixel (TASP) method.
Giraud, Rémi +3 more
openaire +3 more sources