Object-based spectral quality assessment of high-resolution pan-sharpened satellite imageries: new combined fusion strategy to increase the spectral quality

Abstract

Panchromatic and multispectral images produced by the earth observation satellites are fused; hence, a high-resolution multispectral image is obtained. Spectral quality of the fused images is of great importance since the quality of a large number of remote sensing products mainly depends on this feature. Due to the importance of the spectral quality of the fused images, its assessment is of particular significance as well. This article proposes an object-based strategy for the spectral quality assessment of the fused images to eliminate the limitations of the current pixel-based method. This kind of assessment is performed by focusing on homogeneous objects with similar spectral and textural behaviors. After determining an optimal metric, the object-based scheme was applied to five datasets from four types of satellite sensors and the spectral behavior of fusion methods was examined within the image classes. Although the spectral behavior of the fusion methods was not regular, the best methods in each class were determined using statistical analysis. Furthermore, a scheme was proposed to combine the results of different fusion methods to obtain a fused image with the best possible spectral quality. The obtained results indicate that this image enjoys 37% better quality than the best-fused image selected based on the pixel-based quality assessment.