Assessment of the spectral quality of fused images using the CIEDE2000 distance


Image fusion (pan-sharpening) plays an important role in remote sensing applications. Mainly, this process allows to obtain images of high spatial and spectral resolution. However, pan-sharpened images usually present spectral and spatial distortion when comparing with the source images. Because of this, the evaluation of the spectral quality of pan-sharpened images is a fundamental subject to optimize and compare the results of different algorithms. Several assessments of spectral quality have been described in the scientific literature. However, no consensus has been reached on which one describes optimally the spectral distortion in the image. In addition, its performance from the point of view of perceived spectral quality has not been addressed. The aim of this paper is to explore the use of CIEDE2000 distance to evaluate the spectral quality of the fused images. To do this, a database containing remote sensing imagery and its fusion products was created. The spectral quality of the imagery on the database was evaluated using both common quantitative indices and CIEDE2000. With the purpose of determining the relationship between the quantitative indices of spectral quality and the subjective perception of the spectral quality of the merged image, these results were compared to the qualitative assessment provided by a mean opinion score test.

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This work has been supported by the project ARTeMISat-2: Advanced Processing of Remote Sensing Data for Monitoring and Sustainable Management of Marine and Terrestrial Resources in Vulnerable Ecosystems (CTM2016-77733-R), funded by the Spanish Agencia Estatal de Investigación (AEI) and Fondo Europeo de Desarrollo Regional (FEDER).

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Correspondence to Dionisio Rodríguez-Esparragón.

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Rodríguez-Esparragón, D., Marcello, J., Gonzalo-Martín, C. et al. Assessment of the spectral quality of fused images using the CIEDE2000 distance. Computing 100, 1175–1188 (2018).

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  • Image fusion
  • Image quality
  • Quality indicators
  • CIEDE2000
  • Pan-sharpening

Mathematics Subject Classification

  • 94A08