Divide-and-conquer strategies for hyperspectral image processing

A review of their benefits and advantages

Ian Blanes, Joan Serra-Sagristà, Michael W Marcellin, Joan Bartrina-Rapesta

Research output: Contribution to journalReview article

18 Citations (Scopus)

Abstract

In the field of geophysics, huge volumes of information often need to be processed with complex and time-consuming algorithms to better understand the nature of the data at hand. A particularly useful instrument within a geophysicists toolbox is a set of decorrelating transforms. Such transforms play a key role in the acquisition and processing of satellite-gathered information, and notably in the processing of hyperspectral images. Satellite images have a substantial amount of redundancy that not only renders the true nature of certain events less perceivable to geophysicists but also poses an issue to satellite makers, who have to exploit this data redundancy in the design of compression algorithms due to the constraints of down-link channels. This issue is magnified for hyperspectral imaging sensors, which capture hundreds of visual representations of a given targeteach representation (called a component or a band) for a small range of the light spectrum. Although seldom alone, decorrelation transforms are often used to alleviate this situation by changing the original data space into a representation where redundancy is decreased and valuable information is more apparent.

Original languageEnglish (US)
Article number6179815
Pages (from-to)71-81
Number of pages11
JournalIEEE Signal Processing Magazine
Volume29
Issue number3
DOIs
StatePublished - 2012

Fingerprint

Hyperspectral Image
Divide and conquer
Redundancy
Image Processing
Image processing
Satellites
Transform
Geophysics
Hyperspectral Imaging
Satellite Images
Processing
Compression
Sensor
Sensors
Range of data
Strategy
Review

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics

Cite this

Divide-and-conquer strategies for hyperspectral image processing : A review of their benefits and advantages. / Blanes, Ian; Serra-Sagristà, Joan; Marcellin, Michael W; Bartrina-Rapesta, Joan.

In: IEEE Signal Processing Magazine, Vol. 29, No. 3, 6179815, 2012, p. 71-81.

Research output: Contribution to journalReview article

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