scholarly journals MULTISCALE SEGMENTATION OF POLARIMETRIC SAR IMAGE BASED ON SRM SUPERPIXELS

2016 ◽  
Vol XLI-B7 ◽  
pp. 283-287
Author(s):  
F. Lang ◽  
J. Yang ◽  
L. Wu ◽  
D. Li
Keyword(s):  
Object Oriented ◽  
Test Site ◽  
Region Merging ◽  
Polarimetric Sar ◽  
Multi Scale ◽  
Single Scale ◽  
Binary Partition ◽  
Segmentation Algorithms ◽  
Merging Process ◽  
Statistical Region Merging

Multi-scale segmentation of remote sensing image is more systematic and more convenient for the object-oriented image analysis compared to single-scale segmentation. However, the existing pixel-based polarimetric SAR (PolSAR) image multi-scale segmentation algorithms are usually inefficient and impractical. In this paper, we proposed a superpixel-based binary partition tree (BPT) segmentation algorithm by combining the generalized statistical region merging (GSRM) algorithm and the BPT algorithm. First, superpixels are obtained by setting a maximum region number threshold to GSRM. Then, the region merging process of the BPT algorithm is implemented based on superpixels but not pixels. The proposed algorithm inherits the advantages of both GSRM and BPT. The operation efficiency is obviously improved compared to the pixel-based BPT segmentation. Experiments using the Lband ESAR image over the Oberpfaffenhofen test site proved the effectiveness of the proposed method.

scholarly journals MULTISCALE SEGMENTATION OF POLARIMETRIC SAR IMAGE BASED ON SRM SUPERPIXELS

2016 ◽  
Vol XLI-B7 ◽  
pp. 283-287
Author(s):  
F. Lang ◽  
J. Yang ◽  
L. Wu ◽  
D. Li
Keyword(s):  
Object Oriented ◽  
Test Site ◽  
Region Merging ◽  
Polarimetric Sar ◽  
Multi Scale ◽  
Single Scale ◽  
Binary Partition ◽  
Segmentation Algorithms ◽  
Merging Process ◽  
Statistical Region Merging

Multi-scale segmentation of remote sensing image is more systematic and more convenient for the object-oriented image analysis compared to single-scale segmentation. However, the existing pixel-based polarimetric SAR (PolSAR) image multi-scale segmentation algorithms are usually inefficient and impractical. In this paper, we proposed a superpixel-based binary partition tree (BPT) segmentation algorithm by combining the generalized statistical region merging (GSRM) algorithm and the BPT algorithm. First, superpixels are obtained by setting a maximum region number threshold to GSRM. Then, the region merging process of the BPT algorithm is implemented based on superpixels but not pixels. The proposed algorithm inherits the advantages of both GSRM and BPT. The operation efficiency is obviously improved compared to the pixel-based BPT segmentation. Experiments using the Lband ESAR image over the Oberpfaffenhofen test site proved the effectiveness of the proposed method.

scholarly journals Unsupervised TOF Image Segmentation through Spectral Clustering and Region Merging

2018 ◽  
Vol 18 (02) ◽  
pp. e11
Author(s):  
Luciano Lorenti ◽  
Javier Giacomantone ◽  
Oscar Bria
Keyword(s):  
Spectral Clustering ◽  
Similarity Criterion ◽  
Normal Vector ◽  
Region Merging ◽  
Segmentation Method ◽  
Merging Process ◽  
Vector Estimation ◽  
3D Scene ◽  
Statistical Region Merging ◽  
Spectral Clustering Method

Time of Flight (TOF) cameras generate two simultaneous images, one of intensity and one of range. This allows to tackle segmentation problems in which the separate use of intensity or range information is not enough to extract objects of interest from the 3D scene. In turn, range information allows to obtain a normal vector estimation of each point of the captured surfaces. This article presents a semi-supervised spectral clustering method which combines intensity and range information as well as normal vector orientations to improve segmentation results. The main contribution of this article consists in the use of a statistical region merging as a final step of the segmentation method. The region merging process combines adjacent regions which satisfy a similarity criterion. The performance of the proposed method was evaluated over real images. The use of this final step presents preliminary improvements in the metrics evaluated.

Polarimetric SAR Image Segmentation Using Statistical Region Merging

2014 ◽  
Vol 11 (2) ◽  
pp. 509-513 ◽  
Author(s):  
Fengkai Lang ◽  
Jie Yang ◽  
Deren Li ◽  
Lingli Zhao ◽  
Lei Shi
Keyword(s):  
Image Segmentation ◽  
Sar Image ◽  
Region Merging ◽  
Polarimetric Sar ◽  
Sar Image Segmentation ◽  
Statistical Region Merging

An Object-Oriented Analysis of Complex Numerical Models

2014 ◽  
Vol 611-612 ◽  
pp. 1356-1363 ◽  
Author(s):  
Piotr Macioł ◽  
Romain Bureau ◽  
Christof Sommitsch
Keyword(s):  
Numerical Models ◽  
Object Oriented ◽  
Scale Model ◽  
Internal Variables ◽  
Object Oriented Design ◽  
Multi Scale ◽  
Advantages And Disadvantages ◽  
Single Scale ◽  
Scale Models ◽  
Modelling Methodology

Modelling the behaviour of metal alloys during their thermo-mechanical processing relies on the physical and mathematical description of numerous phenomena occurring in several space scales and evolving on different characteristic times. Although it is possible to develop complicated multi-scale models, it is often simpler to simulate each phenomenon separately in a single-scale model and link all the models together in a global structure responsible for their good interaction. Such a structure is relatively difficult to design. Both efficiency and flexibility must be well balanced, keeping in mind the character of scientific computing. In that context, the Agile Multiscale Modelling Methodology (AM3) has been developed in order to support the object-oriented designing of complex numerical models [. In this paper, the application of the AM3 for designing a model of the metal alloy behaviour is presented. The basis and some consequences of the application of the Object-Oriented design of a sub-models structure are investigated. The object-oriented (OO) design of a 3 internal variables model of the dislocations evolution is presented and compared to the procedural one. The main advantages and disadvantages of the OO design of numerical models are pointed out.

scholarly journals OBJECT-ORIENTED CHANGE DETECTION BASED ON MULTI-SCALE APPROACH

2016 ◽  
Vol XLI-B7 ◽  
pp. 517-522
Author(s):  
Yonghong Jia ◽  
Mingting Zhou ◽  
Ye Jinshan
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Change Detection ◽  
Object Oriented ◽  
Remote Sensing Image ◽  
Multi Scale ◽  
Single Scale ◽  
High Resolution Images ◽  
Image Object ◽  
Scale Classification

The change detection of remote sensing images means analysing the change information quantitatively and recognizing the change types of the surface coverage data in different time phases. With the appearance of high resolution remote sensing image, object-oriented change detection method arises at this historic moment. In this paper, we research multi-scale approach for high resolution images, which includes multi-scale segmentation, multi-scale feature selection and multi-scale classification. Experimental results show that this method has a stronger advantage than the traditional single-scale method of high resolution remote sensing image change detection.

Comparative analysis of modern automated algorithms image segmentation

2012 ◽  
Vol 16 (5) ◽  
pp. 37-47
Author(s):  
O.M. Lisenko ◽  
A.YU. Varfolomєєv
Keyword(s):  
Image Segmentation ◽  
Comparative Analysis ◽  
Expectation Maximization ◽  
Mean Shift ◽  
Natural Images ◽  
Region Merging ◽  
Segmentation Algorithms ◽  
Automated Algorithms ◽  
Unsupervised Image Segmentation ◽  
Statistical Region Merging

Unsupervised image segmentation algorithms based on-mean clustering, expectation-maximization, mean-shift, normalized graph cut, weighted aggregation, statistical region merging, JSEG, HGS and ROI-SEG are considered. The results of segmentation obtained by mentioned algorithms on textural, satellite and natural images are presented. The analysis of quality and segmentation speed of each algorithm realization is performed

scholarly journals OBJECT-ORIENTED CHANGE DETECTION BASED ON MULTI-SCALE APPROACH

2016 ◽  
Vol XLI-B7 ◽  
pp. 517-522
Author(s):  
Yonghong Jia ◽  
Mingting Zhou ◽  
Ye Jinshan
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Change Detection ◽  
Object Oriented ◽  
Remote Sensing Image ◽  
Multi Scale ◽  
Single Scale ◽  
High Resolution Images ◽  
Image Object ◽  
Scale Classification

The change detection of remote sensing images means analysing the change information quantitatively and recognizing the change types of the surface coverage data in different time phases. With the appearance of high resolution remote sensing image, object-oriented change detection method arises at this historic moment. In this paper, we research multi-scale approach for high resolution images, which includes multi-scale segmentation, multi-scale feature selection and multi-scale classification. Experimental results show that this method has a stronger advantage than the traditional single-scale method of high resolution remote sensing image change detection.

scholarly journals Object-oriented mapping application of architecture based on multi-scale image segmentation and image extraction

2014 ◽  
Vol XL-4 ◽  
pp. 201-207
Author(s):  
X. Qi ◽  
X. Chen
Keyword(s):  
Arable Land ◽  
Research Work ◽  
Object Oriented ◽  
Extraction Methods ◽  
Region Merging ◽  
Segmentation Method ◽  
Multi Scale ◽  
Traditional Algorithm ◽  
Automatic Mapping ◽  
Extraction Experiment

Residential area detection is extremely important for supervision of rush-built and illegal construction behavior to protect arable land and basic farmland. Traditional manual recognition of illegal construction is simple but time-consuming. The specific research work in the thesis includes: the proposition and designing of a multi-scale segmentation method based on watershed segmentation combined with region merging algorithm, comparative experiments of the new algorithm and traditional algorithm. Then, architecture extraction experiment based on the multi-scale segmentation method is carried out and analysis of the precision of comparative experiment results of pixel-based and object-oriented extraction methods is made, all these steps facilitate the automatic mapping of the architecture.

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