提出三重散射模型，显著提升微焦点双源成像的散射校正精度。

Compared to single-source imaging systems, dual-source imaging systems equipped with two cross-distributed scanning beams significantly enhance temporal resolution and capture more comprehensive object scanning information. Nevertheless, the interaction between the two scanning beams introduces more complex scatter signals into the acquired projection data. Existing methods typically model these scatter signals as the sum of cross-scatter and forward scatter, with cross-scatter estimation limited to single-scatter along primary paths. Through experimental measurements on our selfdeveloped micro-focus dual-source imaging system, we observed that the peak ratio of hardware-induced ambient scatter to single-source projection intensity can even exceed 60%, a factor often overlooked in conventional models. To address this limitation, we propose a more comprehensive model that decomposes the total scatter signals into three distinct components: ambient scatter, cross-scatter, and forward scatter. Furthermore, we introduce a cross-scatter kernel superposition (xSKS) module to enhance the accuracy of cross-scatter estimation by modeling both single and multiple crossscatter events along non-primary paths. Additionally, we employ a fast object-adaptive scatter kernel superposition (FOSKS) module for efficient forward scatter estimation. In Monte Carlo (MC) simulation experiments performed on a custom-designed waterbone phantom, our model demonstrated remarkable superiority, achieving a scatter-toprimary-weighted mean absolute percentage error (SPMAPE) of 1.32%, significantly lower than the 12.99% attained by the state-of-the-art method. Physical experiments further validate the superior performance of our model in correcting scatter artifacts.