In this paper, a novel modification applies to the Band-Dependent Spatial Detail (BDSD) framework to improve the fusion performance interestingly. Joint multiplication terms have been added to the conventional BDSD framework to make it nonlinear BDSD. It has been shown that joint product terms would lead to a better estimation of detail maps for each spectral band. To support the idea presented here, three public domain sensors were selected to conduct the experimental studies. The objective evaluation was performed through no-referenced quality metrics. Based on the visual assessment of fusion products, the developed generalized BDSD (nonlinear BDSD) approach better preserves spectral and spatial information to the fused outcome in comparison to the competitor methods.

在本文中，一种新颖的修改应用于基于波段的空间细节（BDSD）框架，以有趣地改善融合性能。联合乘法项已添加到常规BDSD框架中，以使其成为非线性BDSD。已经表明，联合乘积项将导致更好地估计每个光谱带的细节图。为了支持此处提出的想法，选择了三个公共领域的传感器来进行实验研究。客观评估是通过无参考质量指标进行的。基于融合产品的视觉评估，与竞争对手的方法相比，已开发的广义BDSD（非线性BDSD）方法可以更好地保留融合结果的光谱和空间信息。