Assessing Full-Resolution Pansharpening Quality: A Comparative Study of Methods and Measurements

Abstract

Since the introduction of pansharpening, quality assessment has played a pivotal role in related remote sensing research to ensure the overall system's reliability. Full-resolution (FR) quality assessment is a debated research topic for applications. However, FR assessment faces challenges due to the absence of reference compared to reduced-resolution assessment. Moreover, the lack of ground truth makes measuring quality metrics even more challenging. To summarize the current measures for these two challenges, this article presents a comprehensive study of FR methods. We review various FR techniques and analyze how they extract spatial and spectral features from pansharpened images without reference to high-resolution multispectral images. A classification approach is proposed to group these methods based on their shared characteristics, making it easier for researchers and practitioners to compare and select the most appropriate FR method for specific applications. Furthermore, we provide a summary of strategies for measuring FR performance in the absence of ground truth. These strategies are classified into subjective and objective approaches. In addition, we conduct a board analysis on a large-scale public pansharpened database with unified measuring criteria. This unified analysis allows us to present experiments from a statistical perspective, measure FR protocols' performance, and provide a broad qualitative and quantitative analysis. Overall, this study contributes to the development of pansharpening and provides guidance for selecting appropriate FR methods, as well as strategies for measuring FR performance.

Keywords

• Full-resolution quality assessment
• image quality assessment (IQA)
• pansharpening
• remote sensing