Spectral mapping based on panchromatic block structure analysis

Fusing panchromatic (PAN) and multispectral (MS) images, i.e., pansharpening, can obtain a high-resolution MS (HRMS) image. In this paper, we propose a spectral mapping framework for pansharpening problem based on PAN block structure analysis (PBSA). The PBSA employs boundary, inner uniqueness, and neighborhood comparisons as block structure characteristics to classify the PAN image blocks into pureness composition and mixture composition. For the PAN blocks with pureness composition, they can directly copy the spectral information of corresponding MS pixels. For the mixture PAN blocks, assuming that they can linearly represented by some pure PAN blocks, their spectral signals can get via a weighted average from the relative pure PAN blocks. The experiments on real PAN and MS pairs show that the proposed pansharpening method not only conforms to the structure of the PAN image but also preserves the spectral information of the MS image. The final fused HRMS image shows good performance in visual effect and objective assessment.