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The Tradeoff Analysis for Remote Sensing Image Fusion Using Expanded Spectral Angle Mapper.

Shaohui Chen1, Hongbo Su2, Renhua Zhang3

  • 1Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A, Datun Road, Chaoyang District, Beijing 100101, China. chenshaohu@gmail.com.

Sensors (Basel, Switzerland)
|November 24, 2016
PubMed
Summary
This summary is machine-generated.

Image fusion enhances remote sensing images by combining high-resolution panchromatic images with low-resolution multispectral images. However, improving spatial resolution often compromises spectral properties, a trade-off analyzed in this study.

Keywords:
Expanded Spectral Angle Mapper (ESAM)Image FusionSpatial ImprovementSpectral PreservationTradeoff Analysis

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Area of Science:

  • Remote Sensing
  • Image Processing
  • Geospatial Analysis

Background:

  • Image fusion integrates high-resolution panchromatic images (HRPI) with low-resolution multispectral images (LRMI) to create high-resolution multispectral images (HRMI).
  • Existing fusion techniques face a trade-off between enhancing spatial resolution and preserving spectral properties.

Purpose of the Study:

  • To mathematically analyze the trade-off in remote sensing image fusion.
  • To evaluate the performance of different fusion methods regarding spatial and spectral fidelity.

Main Methods:

  • Mathematical analysis based on a minimization problem.
  • Evaluation of four fusion methods using the Expanded Spectral Angle Mapper (ESAM).

Main Results:

  • All tested fusion methods exhibit the inherent trade-off between spatial resolution improvement and spectral property preservation.
  • The analysis confirms the difficulty in achieving optimal results in both aspects simultaneously.

Conclusions:

  • The trade-off between spatial enhancement and spectral preservation is a fundamental challenge in remote sensing image fusion.
  • Further research is needed to develop fusion techniques that better balance these competing objectives.