High-contrast dual-modal imaging of absorption and scattering using low-rank and sparse matrix decomposition of light fields

Optical absorption and scattering are critical properties of biological tissues, but strong background light often obscures this information, limiting imaging contrast and the visualization of tissue microstructures. Current methods for enhancing imaging contrast rely on image processing and noise suppression, but often lose critical details under strong background light. To address this issue, we propose a dual-modal imaging technique based on a low-rank and sparse matrix decomposition (LRSD) of light fields, enabling simultaneous high-contrast imaging of absorption and scattering and significantly improving imaging performance. Monte Carlo simulation results demonstrate that the low-rank component of the light field effectively separates background light, while the sparse component accurately captures the absorption and scattering properties of the target. In imaging experiments on skin follicle tissues, this method successfully extracted absorption and scattering information, achieving a twofold improvement in imaging contrast, with the SNR improving by 2.97 dB and significantly enhancing the visualization of tissue microstructures. Compared to traditional image filtering methods, the LRSD technique showed superior performance under strong background light conditions. Furthermore, imaging experiments on different regions of rabbit taste bud slices further validated the broad applicability and potential of this method in biological imaging. The high-contrast dual-modal imaging method proposed in this study demonstrates exceptional capabilities in visualizing the tissue structure, offering an innovative solution for the clinical evaluation of pathological sections.