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Quality Assessment for Pansharpening Based on Component Analysis

  • Liangyu Zhou
  • Xiaoyan Luo
  • Xiaofeng Shi
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 875)

Abstract

The quality assessment for pansharpening is important. Since most existing indexes evaluate the performance of entire fused image either from the spatial aspect or the spectral aspect individually, we introduce an pansharpening metric which separate the fused image into two components to evaluate spectral and spatial quality simultaneously. This can be achieved by pure pixels containing one material and mixed pixels with more than one materials in the multispectral (MS) image. The MS pure pixels can be utilized to evaluate the spectral quality, which are projected to the low-frequency regions in the panchromatic (PAN) image. In contrast, the MS mixed pixels corresponding to the PAN high-frequency regions can be utilized to evaluate the spatial quality. Finally, the pansharpening quality assessment is made by a weighted sum of common existing criteria on pure and mixed components, which generates a pure and mixed index (PM index). Experimental results, carried out on high-resolution GeoEye-1 and WV-2 datasets, demonstrate that the proposed quality assessment is made on fused images in a more comprehensive and objective manner.

Keywords

Pansharpening Remote sensing Quality assessment Superpixels 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Image Processing Center, School of AstronauticsBeihang UniversityBeijingChina
  2. 2.School of Electronic and Information EngineeringBeihang UniversityBeijingChina

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