High-quality imaging under low scattering conditions using the light field contribution matrix model

The extraction of singly scattered photons is crucial for achieving high-quality imaging. Singular value decomposition of the optical transmission matrix (TM) can effectively separate singly and multiply scattered photons. However, traditional TM construction methods usually require capturing a large number of light field images, a process that is both time-consuming and complex, limiting its widespread use in practical applications. This paper introduces the light field contribution matrix (LFCM) model, which separates singly and multiply scattered photons using a single light field collection under low scattering conditions, enhancing measurement efficiency and enabling imaging in dynamic environments. Experimental results show that under low scattering conditions with a high proportion of singly scattered photons, the technique doubles the signal-to-noise ratio and increases the contrast by 1.5 times. In fly brain structure imaging experiments, LFCM successfully revealed hidden features and details, demonstrating its advantages in complex structural analysis. Additionally, since the technique is based on light field intensity information imaging, it has potential applications in digital image processing, particularly for reducing image blur caused by scattering, as demonstrated in the case of scatter blur correction of digital images of cataracts in the human eye. Therefore, this method provides a practical and efficient solution for high-quality imaging under low scattering conditions.