  The noise in absorption imaging of cold atoms significantly impacts
measurement accuracy across a range of applications with ultracold atoms. It is
crucial to adopt an approach that offers effective denoising capabilities
without compromising the unique structure of the atoms. Here we introduce a
novel image enhancement algorithm for cold atomic absorption imaging. The
algorithm successfully suppresses background noise, enhancing image contrast
significantly. Experimental results showcase that this approach can enhance the
accuracy of cold atom particle number measurements by approximately tenfold,
all while preserving essential information. Moreover, the method exhibits
exceptional performance and robustness when confronted with fringe noise and
multi-component imaging scenarios, offering high stability. Importantly, the
optimization process is entirely automated, eliminating the need for manual
parameter selection. The method is both compatible and practical, making it
applicable across various absorption imaging fields.
