Journal of Electrical and Computer Engineering

Algorithms for Multispectral and Hyperspectral Image Analysis

Publishing date
07 Sep 2012
Submission deadline
20 Apr 2012

Lead Editor

1US Army Research Laboratory, Adelphi, MD, USA

2Wake Forest University, Winston-Salem, NC, USA

3Space and Remote Sensing Sciences Group, Los Alamos National Laboratory, Los Alamos, NM, USA

4University of Missouri, Columbia, MO, USA

Algorithms for Multispectral and Hyperspectral Image Analysis


Recent advances in multispectral and hyperspectral sensing technologies coupled with rapid growth in computing power have led to new opportunities in remote sensing—higher spatial and/or spectral resolution over broader areas leads to more accurate and comprehensive land cover mapping and more sensitive target detection. But these large volumes of data provide new challenges as well. The need for timely processing of this data creates a tension between simplicity and sophistication of algorithms and motivates the development of parallel algorithms and specialized hardware. Critical issues in the analysis of multispectral and hyperspectral data include sensor noise and nonlinearities, atmospheric distortion and interference, characterization of target signatures and variability of background clutter, combination of spatial and spectral features, and the balance of statistical and physical modeling.

Despite a plethora of hyperspectral algorithms developed over the last decade, most of these issues still remain. Accordingly, the development of robust and accurate modeling and analysis of multispectral and hyperspectral imagery are essential for advancing the quality of information retrieval from a remote sensor or suite of sensors. This special issue aims to advance the capabilities of algorithms and analysis technologies for this imagery by addressing these critical issues.

Investigators are invited to submit their original contributions that can address the current multispectral and hyperspectral signal processing issues. Timely review papers will also be considered. Potential topics include, but are not limited to:

  • Novel algorithms for supervised classification
  • Semisupervised classification and rare category detection
  • Anomaly detection, unsupervised classification, segmentation, and clustering
  • Dimensionality reduction
  • Material detection, identification, and quantitation
  • Physics-based modeling
  • Sensor fusion
  • Spectral unmixing, endmember extraction
  • Spatiospectral feature extraction
  • Fast implementation of multispectral and hyperspectral algorithms
  • Compressive sensing (and reconstruction) of multispectral/hyperspectral data
  • Signal processing directly on compressively sensed hyperspectral data

Before submission authors should carefully read over the journal's Author Guidelines, which are located at Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at according to the following timetable:


  • Special Issue
  • - Volume 2013
  • - Article ID 908906
  • - Editorial

Algorithms for Multispectral and Hyperspectral Image Analysis

Heesung Kwon | Xiaofei Hu | ... | Prudhvi Gurram
  • Special Issue
  • - Volume 2012
  • - Article ID 425947
  • - Research Article

A Semiparametric Model for Hyperspectral Anomaly Detection

Dalton Rosario
  • Special Issue
  • - Volume 2012
  • - Article ID 162106
  • - Research Article

Hyperspectral Anomaly Detection: Comparative Evaluation in Scenes with Diverse Complexity

Dirk Borghys | Ingebjørg Kåsen | ... | Christiaan Perneel
  • Special Issue
  • - Volume 2012
  • - Article ID 818175
  • - Research Article

Non-Gaussian Linear Mixing Models for Hyperspectral Images

Peter Bajorski
  • Special Issue
  • - Volume 2012
  • - Article ID 409357
  • - Research Article

Randomized SVD Methods in Hyperspectral Imaging

Jiani Zhang | Jennifer Erway | ... | Robert Plemmons
  • Special Issue
  • - Volume 2012
  • - Article ID 103286
  • - Research Article

Evaluating Subpixel Target Detection Algorithms in Hyperspectral Imagery

Yuval Cohen | Yitzhak August | ... | Stanley R. Rotman
  • Special Issue
  • - Volume 2012
  • - Article ID 628479
  • - Research Article

Target Detection Using Nonsingular Approximations for a Singular Covariance Matrix

Nir Gorelik | Dan Blumberg | ... | Dirk Borghys
Journal of Electrical and Computer Engineering
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Acceptance rate11%
Submission to final decision88 days
Acceptance to publication16 days
Journal Citation Indicator0.480
Impact Factor2.4
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