2015
DOI: 10.5120/19208-0915
|View full text |Cite
|
Sign up to set email alerts
|

A Novel Adaptive Compression Technique for Dealing with Corrupt Bands and High Levels of Band Correlations in Hyperspectral Images Based on Binary Hybrid GA-PSO for Big Data Compression

Abstract: Hyperspectral sensors generate useful information about climate and the earth's surface in numerous contiguous narrow spectral bands, being widely used in resource management, agriculture, environmental monitoring, among others. The compression of hyperspectral data helps in long-term storage and transmission systems. This paper introduces a new adaptive compression method for hyperspectral data. The method is based on separating the bands with different specifications by the histogram analysis and Binary Hybr… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
1
0

Year Published

2015
2015
2017
2017

Publication Types

Select...
2
2
1

Relationship

0
5

Authors

Journals

citations
Cited by 5 publications
(6 citation statements)
references
References 17 publications
0
1
0
Order By: Relevance
“…In addition, the concept of PSO and FODPSO has been used for other applications such as image clustering, classification, data compression, and feature selection in the remote-sensing community. For more information on other applications of the PSO family, we refer interested readers to (Ghamisi et al 2013(Ghamisi et al , 2015a(Ghamisi et al , 2015bKargozar Nahavandi et al 2015 andGhamisi andBenediktsson 2015) …”
Section: Problem Formulationmentioning
confidence: 99%
“…In addition, the concept of PSO and FODPSO has been used for other applications such as image clustering, classification, data compression, and feature selection in the remote-sensing community. For more information on other applications of the PSO family, we refer interested readers to (Ghamisi et al 2013(Ghamisi et al , 2015a(Ghamisi et al , 2015bKargozar Nahavandi et al 2015 andGhamisi andBenediktsson 2015) …”
Section: Problem Formulationmentioning
confidence: 99%
“…Ghamisi et al proposed the HGAPSO method [3,4]; consisting of two main portions: one is for combining the standard velocity and another is for updating the rules of PSOs (Particle Swarm Optimization) with the ideas of collection, crossover and transfiguration from GA (Genetic Algorithm) [5]. We have used HGAPSO instead of Otsu because for an obvious reason.…”
Section: Literature Reviewmentioning
confidence: 99%
“…In [3,4], Ghamisi et al proposed the HGAPSO method; which has two main parts. One is to the association of the standard velocity and with the planning of selection, crossover and mutation from GA [5]; another one is to update the procedure of Particle Swarm Optimization. Swarm or population is the set of solutions from PSO; in which each solution consists of a set of parameters and represents a point in the multidimensional space, denoted as a particle [21].…”
Section: A Apply Hgapsomentioning
confidence: 99%
See 2 more Smart Citations