Quality Assessment of Panchromatic and Multispectral Image Fusion for the ZY-3 Satellite: From an Information Extraction Perspective

Abstract

The first results of multispectral (MS) and panchromatic (PAN) image fusion for the ZiYuan-3 (ZY-3) satellite, which is China's first civilian high-resolution satellite, are announced in this study. To this end, the various commonly used image fusion (pan-sharpening) techniques are tested. However, traditionally, image fusion quality is assessed by measuring the spectral distortion between the original and the fused MS images. The traditional methods focus on the spectral information at the data level but fail to indicate the image content at the information level, which is more important for specific remote sensing applications. In this context, we propose an information-based approach for assessing the fused image quality by the use of a set of primitive indices which can be calculated automatically without a requirement for training samples or machine learning. Experiments are conducted using ZY-3 PAN and MS images from Wuhan, central China. One of the objectives of the experiments is to investigate the appropriate image fusion strategies for the ZY-3 satellite at both the data and information levels. On the other hand, the experiments also aim to reveal the inadequacy of the traditional image quality indices and the advantages of the proposed information indices for describing image content. It is suggested that an appropriate image quality index should take into account the global and local image features at both the data and information levels.