Imaging quality comparison of two typical methods for imaging through turbid media

Abstract

Due to the multiple scattering of light in turbid media such as biological tissues, the image of target becomes highly deteriorated and even disappears entirely. Only speckle patterns, which result from multiple scattering and interference in turbid media and contain disordered objects-information, can be acquired. Two typical methods to recover the image of target behind a turbid medium are described and simulated in this paper. The first approach is based on image correlation and wavefront shaping technique, in which the Pearson correlation coefficient is applied as a cost function for the optimization and genetic algorithm (GA) is employed to control a spatial light modulator to generate the optimal wavefront to maximize the cost function. For the second approach, the target images can be reconstructed from the speckle patterns with total variation minimization by augmented Lagrangian and alternating direction algorithms (TVAL3). Circular Gaussian distribution model and Fresnel diffraction theory are exploited in our simulations to describe turbid media and light propagation between optical devices, respectively. The anti-noise capabilities of the two methods are analyzed to demonstrate their stabilities applied in low signal-to-noise environment. This work will be beneficial to the fields of microscopic imaging and biomedical imaging in micro/nano scale.