Multidimensional local spatial autocorrelation measure for integrating spatial and spectral information in hyperspectral image band selection

Du, Ziyun; Jeong, Young-Seon; Jeong, Myong K.; Kong, Seong G.

doi:10.1007/s10489-010-0274-8

Cited by 13 publications

(3 citation statements)

References 19 publications

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“…It may occasionally yield spurious assignments of pixels to classes. To avoid this issue, we may apply the principle of local auto-correlation congruence of objects (Appice et al, 2016(Appice et al, , 2017Du et al, 2012;, according to which detected clusters, comprising changed objects, generally expand across contiguous areas (Appice et al, 2015). Based on this principle, we may decide to change the assignment of pixels that strongly disagree with surrounding assignments.…”

Section: I=1mentioning

confidence: 99%

Leveraging autoencoders in change vector analysis of optical satellite images

et al. 2021

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Various applications in remote sensing demand automatic detection of changes in optical satellite images of the same scene acquired over time. This paper investigates how to leverage autoencoders in change vector analysis, in order to better delineate possible changes in a couple of co-registered, optical satellite images. Let us consider both a primary image and a secondary image acquired over time in the same scene. First an autoencoder artificial neural network is trained on the primary image. Then the reconstruction of both images is restored via the trained autoencoder so that the spectral angle distance can be computed pixelwise on the reconstructed data vectors. Finally, a threshold algorithm is used to automatically separate the foreground changed pixels from the unchanged background. The assessment of the proposed method is performed in three couples of benchmark hyperspectral images using different criteria, such as overall accuracy, missed alarms and false alarms. In addition, the method supplies promising results in the analysis of a couple of multispectral images of the burned area in the Majella National Park (Italy).

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Section: I=1mentioning

confidence: 99%

Leveraging autoencoders in change vector analysis of optical satellite images

et al. 2021

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“…Applications on the field of image segmentation can be found in recent years [19,30,32]. Several methods using a tree structured framework have been applied to high dimensional data, such as hyperspectral images, using the MaxCut problem as a tool for constructing that hierarchical tree [24,27].…”

Section: Practical Issuesmentioning

confidence: 99%

Designing heterogeneous distributed GAs by efficiently self-adapting the migration period

Salto

Alba

2011

Appl Intell

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This paper investigates a new heterogeneous method that dynamically sets the migration period of a distributed Genetic Algorithm (dGA). Each island GA of this multipopulation technique self-adapts the period for exchanging information with the other islands regarding the local evolution process. Thus, the different islands can develop different migration settings behaving like a heterogeneous dGA. The proposed algorithm is tested on a large set of instances of the Max-Cut problem, and it can be easily applied to other optimization problems. The results of this heterogeneous dGA are competitive with the best existing algorithms, with the added advantage of avoiding timeconsuming preliminary tests for tuning the algorithm.

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“…Although the relational language SQL is mature and wellestablished, it is not effective enough to query fuzzy spatiotemporal data. In terms of querying time, fuzzy data or fuzzy spatiotemporal data are imposing strict restrictions on structure [4,33] and data types [9,11] of spatiotemporal data so that the execution time may involve unnecessary querying time on complex structure. In terms of memory cost, relational data is "dense" [5], which means every row has a value in every column, and a "null" value is needed for missing or inapplicable data.…”

Section: Introductionmentioning

confidence: 99%

Querying fuzzy spatiotemporal data using XQuery

Bai

2014

ICA

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How to accurately handle querying criteria based on user's preferences has become a key technology for querying fuzzy spatiotemporal data, typically collected by modern monitoring devices such as GPS receivers and sensors. However, although fuzzy logic is incorporated in querying fuzzy spatiotemporal data and querying fuzzy data in XML, relatively little work has been carried out in querying fuzzy spatiotemporal data in XML. In this paper, we propose an approach for querying fuzzy spatiotemporal data using XQuery. On the basis of its architecture, we make extensions to XQuery language. The extensions consist of the new xs: truth data type intended to represent gradual truth degrees, and the new Val element and the new Poss attribute to handle satisfaction degrees. Furthermore, fuzzy spatiotemporal linguistic terms are extended to declare fuzzy terms and use them in querying expressions. Additionally, FLWOR are extended to support fuzzy spatiotemporal queries. After extensions of XQuery on fuzzy spatiotemporal data, we present real case querying examples, discuss crucial details of their processing, and perform evaluations of each querying example. Finally, the comparative study demonstrates the advantages of our approach.

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Multidimensional local spatial autocorrelation measure for integrating spatial and spectral information in hyperspectral image band selection

Cited by 13 publications

References 19 publications

Leveraging autoencoders in change vector analysis of optical satellite images

Leveraging autoencoders in change vector analysis of optical satellite images

Designing heterogeneous distributed GAs by efficiently self-adapting the migration period

Querying fuzzy spatiotemporal data using XQuery

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